diff --git a/benchmark/benchmark_300K.ipynb b/benchmark/benchmark_300K.ipynb
deleted file mode 100644
index 2560ce9..0000000
--- a/benchmark/benchmark_300K.ipynb
+++ /dev/null
@@ -1,376 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from matplotlib import pyplot as plt\n",
-    "\n",
-    "from utilities import complete_panel, myblue, myred"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "paths = [\"lammps_25part_1.7nm3_300K_NVT/\", \"python_25part_1.7nm3_300K_NVT/\"]\n",
-    "legends = [\"LAMMPS\", \"Python\"]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1700x1000 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(17,10))\n",
-    "\n",
-    "ax = []\n",
-    "n = 0\n",
-    "l_tot = 1\n",
-    "c_tot = 1\n",
-    "\n",
-    "x_boundaries = 0, 0.06\n",
-    "x_ticks = [0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06]\n",
-    "y_boundaries = 0, 0.06\n",
-    "y_ticks = [0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06]\n",
-    "\n",
-    "n += 1\n",
-    "ax.append(plt.subplot(l_tot, c_tot, n))\n",
-    "\n",
-    "for path, legend, color, symbol in zip(paths, legends, [myred, myblue], [\"s\", \"o\"]):\n",
-    "    dump = path + \"dump.lammpstrj\"\n",
-    "    file = open(dump, \"r\")\n",
-    "    velocity = []\n",
-    "    norm_velocity = []\n",
-    "    for line in file:\n",
-    "        try:\n",
-    "            id, type, x, y, z, vx, vy, vz = np.float32(line.split())\n",
-    "            velocity.append([vx, vy, vz])\n",
-    "            norm_velocity.append(np.sqrt(vx**2+vy**2+vz**2))\n",
-    "        except:\n",
-    "            pass\n",
-    "\n",
-    "    proba, vel = np.histogram(norm_velocity[100:], bins=50, range=(x_boundaries))\n",
-    "    vel = (vel[1:]+vel[:-1])/2\n",
-    "    proba = proba/np.sum(proba)\n",
-    "\n",
-    "    ax[-1].plot(vel, proba, symbol, color=color, markersize=15, label=legend)\n",
-    "\n",
-    "plt.xlim(x_boundaries)\n",
-    "plt.xticks(x_ticks)\n",
-    "plt.ylim(y_boundaries)\n",
-    "plt.yticks(y_ticks)\n",
-    "\n",
-    "complete_panel(ax[-1], r'$|v|$ (\\AA/fs)', r'$p (|v|)$', legend=True, title=\"25 particles in 1.7 nm$^3$ at 300 K\")\n",
-    "\n",
-    "fig.tight_layout()\n",
-    "plt.savefig('velocity_distribution_300K.png', bbox_inches = 'tight', pad_inches = 0.062)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 2000x1000 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(20,10))\n",
-    "\n",
-    "ax = []\n",
-    "n = 0\n",
-    "l_tot = 1\n",
-    "c_tot = 2\n",
-    "\n",
-    "x_boundaries = -0.6, 0.2\n",
-    "x_ticks = [-0.6, -0.4, -0.2, 0.0, 0.2]\n",
-    "y_boundaries = 0, 0.15\n",
-    "y_ticks = [0, 0.05, 0.1, 0.15]\n",
-    "\n",
-    "n += 1\n",
-    "ax.append(plt.subplot(l_tot, c_tot, n))\n",
-    "\n",
-    "for path, legend, color, symbol in zip(paths, legends, [myred, myblue], [\"s\", \"o\"]):\n",
-    "    data = path + \"Epot.dat\"\n",
-    "    file = open(data, \"r\")\n",
-    "    steps, Epot = np.loadtxt(file).T\n",
-    "\n",
-    "    proba, energy = np.histogram(Epot, bins=50, range=(x_boundaries))\n",
-    "    energy = (energy[1:]+energy[:-1])/2\n",
-    "    proba = proba/np.sum(proba)\n",
-    "\n",
-    "    ax[-1].plot(energy, proba, symbol, color=color, markersize=15, label=legend)\n",
-    "\n",
-    "plt.xlim(x_boundaries)\n",
-    "plt.xticks(x_ticks)\n",
-    "plt.ylim(y_boundaries)\n",
-    "plt.yticks(y_ticks)\n",
-    "\n",
-    "complete_panel(ax[-1], r'$E_\\textrm{pot}$ (kcal/mol)', r'$p (E_\\textrm{pot})$', legend=True)\n",
-    "\n",
-    "x_boundaries = 20, 24\n",
-    "x_ticks = [20, 21, 22, 23, 24]\n",
-    "y_boundaries = 0, 0.2\n",
-    "y_ticks = [0, 0.05, 0.1, 0.15, 0.2]\n",
-    "\n",
-    "n += 1\n",
-    "ax.append(plt.subplot(l_tot, c_tot, n))\n",
-    "\n",
-    "for path, legend, color, symbol in zip(paths, legends, [myred, myblue], [\"s\", \"o\"]):\n",
-    "    data = path + \"Ekin.dat\"\n",
-    "    file = open(data, \"r\")\n",
-    "    _, Ekin = np.loadtxt(file).T\n",
-    "\n",
-    "    proba, energy = np.histogram(Ekin[10:], bins=50, range=(x_boundaries))\n",
-    "    energy = (energy[1:]+energy[:-1])/2\n",
-    "    proba = proba/np.sum(proba)\n",
-    "\n",
-    "    ax[-1].plot(energy, proba, symbol, color=color, markersize=15, label=legend)\n",
-    "\n",
-    "plt.xlim(x_boundaries)\n",
-    "plt.xticks(x_ticks)\n",
-    "#plt.ylim(y_boundaries)\n",
-    "#plt.yticks(y_ticks)\n",
-    "\n",
-    "complete_panel(ax[-1], r'$E_\\textrm{kin}$ (kcal/mol)', r'$p (E_\\textrm{kin})$', legend=True)\n",
-    "\n",
-    "fig.tight_layout()\n",
-    "plt.savefig('energies_300K.png', bbox_inches = 'tight', pad_inches = 0.062)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 2000x1000 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(20,10))\n",
-    "\n",
-    "ax = []\n",
-    "n = 0\n",
-    "l_tot = 1\n",
-    "c_tot = 1\n",
-    "\n",
-    "x_boundaries = 525, 650\n",
-    "x_ticks = [525, 550, 575, 600, 625, 650]\n",
-    "y_boundaries = 0, 0.3\n",
-    "y_ticks = [0, 0.1, 0.2, 0.3]\n",
-    "\n",
-    "n += 1\n",
-    "ax.append(plt.subplot(l_tot, c_tot, n))\n",
-    "\n",
-    "for path, legend, color, symbol in zip(paths, legends, [myred, myblue], [\"s\", \"o\"]):\n",
-    "    data = path + \"pressure.dat\"\n",
-    "    file = open(data, \"r\")\n",
-    "    steps, press = np.loadtxt(file).T\n",
-    "\n",
-    "    proba, pressure = np.histogram(press[10:], bins=50, range=(x_boundaries))\n",
-    "    pressure = (pressure[1:]+pressure[:-1])/2\n",
-    "    proba = proba/np.sum(proba)\n",
-    "\n",
-    "    ax[-1].plot(pressure, proba, symbol, color=color, markersize=15, label=legend)\n",
-    "\n",
-    "plt.xlim(x_boundaries)\n",
-    "plt.xticks(x_ticks)\n",
-    "plt.ylim(y_boundaries)\n",
-    "plt.yticks(y_ticks)\n",
-    "\n",
-    "complete_panel(ax[-1], r'$p$ (atm)', r'$p (p)$', legend=True)\n",
-    "\n",
-    "fig.tight_layout()\n",
-    "plt.savefig('pressures_300K.png', bbox_inches = 'tight', pad_inches = 0.062)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "paths = [\"lammps_mu2_1.7nm3_300K_GCMC/\", \"python_mu2_1.7nm3_300K_GCMC/\"]\n",
-    "legends = [\"LAMMPS\", \"Python\"]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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mek8qor834ku/FtHXm3yNAAAA1Xh24I64/2Nfizd6fiS2eqr7R8pmT38Uoyfu/9jX4vE//WDcvvZMg6oEAKCTCMYBaGnrGxGPfD1iLhuRf7m0R3ZfbykgTqUiNjZLe29n3lFacvyBD5WC5E5z+7mIRz8Tcf8XI9Y3Iza3Kj+2t6cUij/6mVI7AAAAzbSe6otPfeQrsd7TX3Uovm2rpzfWoz8+/ZFH4vE/+WD0J1wjAACdx1LqALSsZ1+MGP18xOf+OOL5l0vPFaMUDG9slf67PXn6+ZdLrxv9fOm4TnTPbRGP/1Yp3E5F6eMo26+5/VzpuHtua3yNAAAAx3nkwuX49pmLsdlTX5y92dMfz5z52XjkwuWEKgMAoJMJxgFoSd94rrR0+NWXSuH3cauHb7/m6kul477xXONrbIbbz0U8/psRv/vPIt73jtJzqSjNCO97c2b4dmCeeWfpdY//ppniAABAaygWI+Z+5jcSbXP+js9EsYYtpwAA6C4duNgsAO3u2RdLS4a/sVH9ftqbW6U3Wu7/4luzqztNf1/EJ38x4lc/EvHN77617/rrb0Scvumtfdc/8J7O3XcdAABoT09fOx35t/10Yu0VUz2xkr4tvnnt2biYWKsAAHQiwTgALWV9I+JTf1BaJr3aUHzbVrF0/Kf/sDRbuhP3HI8ohd4Xz5c+AAAA2sFTL/9YpIpbUUwlt5BlqrgVT73yo4JxAACOZCl1AFrKI1+P+PYLpZnf9djcinjmu6X2AAAAaA1X105F39ZGom32bW3E1eunE20TAIDOIxgHoGUUixFz2WTbnL8S9poDAABoETc2eqKY8J5PxYh4fcPbnAAAHM2IEYCW8fRqRP7l0psaSShGxMp/K+3DDQAAQPOd6tuKVMJ3L6ci4nRfncuOAQDQ8Tp011UA2tFT3ym9oZHkWySpN9u1DzcAAEDzXRi4ERs9yb4ludHTFxfOvJ5omydqdTXi2rXk2jt7NuK8fwQDAOwnGAegZVx9KaKvN2J9M7k2+3pL7QIAANB8d77j76OYSnYRy2KqJ+58+w8TbfPErK5G3HZbxI0bybV56lTEc88JxwEA9rGUOgAt48Z68vuBF4sRr7+RbJsAAADU5uKFH4vMa/8lUsVklj5PFbdi8LW/jQ9c+LFE2jtx164lG4pHlNpLcgY6AECHEIwD0DJO9UekUsm2mUpFnL4p2TYBAACoTeonz8fkfbck94+/VCom7jsbqZ80OxoAgKMJxgFoGRfeHbGR4DLqEaX2Lrw72TYBAACo3QP/+Ey8/9ZU9Nb5zmRvT8Qd70nFJz5+JpnCAADoaIJxAFrGne+NSHgl9Si+2S4AAACtob8v4su/HtHfG9FT48TxnlTp+C/9WkRfb7L1AQDQmQTjALSMi+cjMu+ISGo19VREDL4z4gPvSahBAAAAEnH7uYhHPxNxU19UPXO8t6d03KOfKbUDAACVEIwD0DJSqYjJkWTbnLiU/L7lAAAA1O+e2yIe/61SuJ2K42+S3n7N7edKx91zW+NrBACgcwjGAWgpD3wo4v23Vj9jYL/SXnMRn/hwMnUBAACQvNvPRTz+mxG/+88i3veO0nOpKC2T3tdT+u92YJ55Z+l1j/+mmeIAAFSvr9kFAMBu23vNffTzEcVixFYNm47baw4AAKB99PdFfPIXI371IxHf/G7EU9+JuPpSxOtvRJy+KeLCuyPufG9pmywrggEAUCvBOAAtZ3uvufu/GLG+GbG5VfmxvW/OKLDXHAAAQHtJpSIuni99AABA0iylDkBLstccAAAAAACQFDPGAWhZ23vNPfL1iLlsRP7lUvjd11taZj2VitjYjChGaa+5iUulPcr7Xd0AAAAAAIBdRAcAtJbV1Yhr13Ye9kfEJ98W8av/NOKb107HU6/8aFy9fjpe3+iJ031bceHM63Hn238YHzj7emmvuaf3tXf2bMR56/ABAAAAAEA3E4wD0DpWVyNuuy3ixo0Dn0pFxMU3P6py6lTEc88JxwEAAGgrxYh4+pafi6fefndcHbgjbvSejlObr8eFtWfizleeiIuv/vWx244BAPAWwTgArePatbKheF1u3Ci1KxgHAACgDayn+uKRC5dj7md+I/Jv++lIFbeib2sjiqlUpIrF2Ojpi2KqJzLf/9uY/NbvxQNXH47+4kazywYAaHk9zS4AAAAAAICIZwfuiNFffiI+9/O/H8/f/FMREVFM9cR6702x0dMf6703RTFVekv3+Zt/Kj73878fo7/8RDw7cEczywYAaAuCcQAAAACAJvvGT3w4Pvrxv4qrA3dEMdWzE4AfZvs1VwfuiI9+/K/iGz/x4ROqFACgPQnGAQAAAACa6NmBO+L+j30t3uj5kdjs6a/q2M2e/nij50fi/o99zcxxAIAjCMYBAAAAAJpkPdUXn/rIV2K9pz+2enpramOrpzfWe/rj0x95JNZTfQlXCADQGQTjAAAAAABN8siFy/HtMxernim+32ZPfzxz5mfjkQuXE6oMAKCzCMYBAAAAAJqgeMvZmPvAv0y0zfkP/EYUbzmbaJsAAJ3AujoAAAAAAE3wdJyP/M3JtVdM9cTKzT8d30xFXEyuWQCAjmDGOAAAAABAEzz1nYhUwm2m3mwXAIC9BOMAAAAAAE1w9aWIvt5k2+zrLbULAMBellIHaEHFYsTTq6U7vK++FHFjPeJUf8SFd0fc+d6Ii+cjUknfUg4AAACcqBvrpfcAklQsRrz+RrJttgrvlwAA9RCMA7SQ9Y2IR74eMZeNyL9cWv6sr7f0D79UKmJjM6IYEZl3REyORDzwoYh+f8kBAACgLZ3qTz7ITaUiTt+UbJvN5v0SACAJhgcAzbS6GnHtWkREPPvqqfjUlffGt189/eYnU1GMiPXNg4c9/3IxPvfHEf/hf3s9vnzpO3H7LTdKnzh7NuL8+RMpHQAAAKjPhXeXQt0kbWyW2u0Uz74Y8ak/iPj2C289d/j7JVF6v+QvIr786xG3nzuxMgGANiAYB2iW1dWI226LuHEjvvETH477P/a1WO/pj2LP8beKF6P0mquv9MdH//i98eif/VLc83d/EXHqVMRzzwnHAQAAoA3c+d5SyJuk4pvtdoJvPBdx/xdLIXgl52n7NVdfivjo5yMe/UzEPbc1skJakSX3ATiMYBygWa5di7hxI54duCPu/9jX4o2eH4mtnt6qmtjs6Y9i9MT9H/taPP6nH4zb154ptSsYBwAAgJZ38Xxp+e/nX04mIE9FROadER94TwKNNdmzL5ZC8Tc2IraqPDmbW6Vw9P4vRjz+W2aOdwtL7gNwnJ5mFwDQzdZTffGpj3wl1nv6qw7Ft2319MZ6T398+iOPxHrKaB4AAADaRSpVCuiSNHGp/WfDrj+/Gp/6n34Y6xvFqkPxbVvFiPWNYnz6f/phrD+/mmyBtJxnX4wY/XxpKf3nXy49t73k/sbW3lUHtpfcH/186TgAuodgHKCJHrlwOb595mJs9vTX1c5mT388c+Zn45ELlxOqDAAAADgJD3wo4v23RvTW+U5tb0/EHe+J+MSHk6mraVZX45Ff/nfx7WunYrNYX8K/WUzFM9dOxSO//O9KW9rRkb7xXGnp/KsvlcLv4+6l2H7N9pL733iu8TUC0BoE4wBNUixGzP3MbyTa5vwdn4li0puTAQAAAA3T3xfx5V+P6O+N6KkxB+5JlY7/0q+Vlo5uZ8VXrsXcbf/3RNuc/+lPR/GVa4m2SWvYveT+5lZ1x25ulY67/4tmjgN0C8E4QJM8fe105N/201FMJfOnuJjqiZX0bfHNa6cTaQ8AAAA4Gbefi3j0MxE39VU/c7y3p3Tco5/pjL20vV9CpdY3Ij71B6Vl0utacn8z4tN/WGoPgM4mGD9hhUIh8vl8s8uoSTNrb+fzBod56uUfi1SxyltZj5EqbsVTr/xoom2eqLNnI06dSrbNU6dK7QIAAEALu+e2iMd/qxRup6L0cZTt19x+rnTcPbc1vsaT4P0SKvXI1yO+/UL1M8X329yKeOa7pfYA6Gx9zS6g02Wz2Zibm4tcLlc22B0aGor77rsvJiYmIp1On3yBR2hm7e183qBSV9dORd/WRqz33pRYm31bG3H1ehvfAX3+fMRzz0VcS3B5s7NnS+0CAABAi7v9XMTjv1kK6OayEfmXS+F3X29pS7ZUKmJjs7Q/cuadEROXSnuU93fQu7zeL6ESxWLpdyRJ81cifvUjpd8zADpTqli0G20jLC4uxuXLl6NQKFR8zNTUVMzMzDSuqAo1s/aT6vvWW2+NF198Mc6dOxcvvPBClVVCMv7lF67Fo8+8LTZ6+hNrs2/zjbj/Z16L//GzZkgDAABAOysWI7753YinvhNx9aWI19+IOH1TxIV3R9z53ogPvKczAzzvl1CJv/mvESP/Nvl2r/yriIvmVwAtSrZVvw66l7A1FAqFuHz5ciwuLu48NzU1Fffdd19kMplIp9ORz+cjm83GzMzMntnQs7Ozkc1m48qVK02ZBd3M2tv5vEGtTvVtRSrhe5NSEXG6L9nlxgAAAICTl0qVArpuC+m8X3KI1VUr7O3y1HdK39ckf1JSb7bbbb9zAN3EjPGEDQ4O7oS2mUwmlpeXjwxrJycnY35+fs9zQ0NDsby83Mgyy2pm7Sfdt7tqaAX/yyOr8f/832+NYqonsTZTxa34/3zku/GJX/nJxNoEAAAAOCneLyljdTXittsibtxIrs1Tp0rb2bVpOP7g/zfif/nzYqxvJbdsQn9PMf5vv5iK//f9iTUJkCjZVv2SG10Q4+PjO+FuOp0+NtyNiJibm4uxsbE9z+VyuZicnGxUmWU1s/Z2Pm9Qjzvf8feJ/iMvIqKY6ok73/7DRNsEAAAAOCneLynj2rVkQ/GIUntJzkA/YTfW/nsUNzYSbbO4sR6vX//vibYJQGsRjCdkdnZ2zzLgDz/8cMXLej/88MMHnpufn9+zXHgjNbP2dj5vUK+LZ1+PzPf/NlLFZJbyShW3YrDwXHzg7OuJtAcAAABw0rxfQiVObfww+SX3ixGnN9r4BgoAjiUYT0ChUIjp6emdx5lM5sBs5qOk0+mYmpo68PzuNhulmbW383mDJKRSEZPf+r1E25x45ouRSm4FKQAAAIAT5f0SKnFh4EZs9PQl2uZGT19cOOMGCoBOluyVo0s99NBDex7Xspz3gw8+GLOzs3ueW1xcjHw+H5lMpq76jtLM2pvV9+rqarz22msREfHaa6/F6upqnG/TvXQ6SbEY8fRqxFPfibj6UsSN9YhT/REX3h1x53sjLp6PjvwHzANXH47/cGEirg7cEZs9/TW307u1HrevfSs+cXU+In49uQIBaFurq6vxR3/0RzuPP/nJTxrzAAAdx5inM3m/hONYcr+M1dWyy+MXixFPXzsdT738Y3F17VTc2OiJU31bcWHgRtz5jr+Pi2dfL/++69mzbbsH/Y5DzknNOuGc0LZkW8kQjNepUCgcCGarmfW8LZ1Ox9DQUORyuT3PLy4ulp0VnYRm1t7MvldXV+MHP/hBRET84Ac/8MejydY3Ih75esRcNiL/ckQqIvp6SwO2VCpiYzOiGBGZd0RMjkQ88KGI/g76y9Vf3Igv//mvxEc//ldRjJ7Y6umtuo2erc3o31qPL/35A9FX3GxAlQC0o9XV1fid3/mdnccjIyPGPABAxzHm6UzeL+E420vuP3/zTyUSkKeKW5H5/n9p3yX3V1cjbrttz17066m+eOTC5Zj7md+I/Nt+OlLFrejb2ohiKhWpYjE2evqimOqJzPf/Nia/9XvxwNWHo7+4a9/2U6cinnuufYPgMuekbu1+Tmhrsq1kWEq9Ttlsds/jdDpd8wzvkZGRA88tLS3V1FYlmll7O5+3qqyuRuRyyX2srjb7K6rfrnPy7NK3Y/S3fxif++NiPP9yaU+gYkSsb0ZsbJX+u71T0PMvF+Nzf1yM0d/+YTy79O2OOie3rz0Tj/7ZL8VNW/8QvVvrVR3bu7UeN239Qzz6Z78Ut68906AKAQAAAE6W90s4iiX397l2bU8A/OzAHTH6y0/E537+9+P5m38qIkoz4td7b4qNnv5Y771p54aC52/+qfjcz/9+jP7yE/HswB1vtXnjRrKzrU/avnOSiHY/J4AZ4/V67LHH9jy+6667am5rdHT0wCzq/QFykppZezuft4odcUdaMSKevuXn4qm33x1XB+6IG72n49Tm63Fh7Zm485Un4uKrfx1lx2DtfkfarnPyjZ/4cNz/sa/Fek9/FHuOH3EW3zwjV1/pj4/+8Xvj0T/7pbjn7/6i/c/Jm+75u7+Ix//0g/HpjzwSz5z52YiII+92TRW3IiLi9rVvxZf+/AH/yAMAAAA6jvdLjlfz+4wdwJL75e1537WC2fTbr7k6cEd89ON/9db7rh2sm39vLLlfhnPSVQTjddofwA4NDdXc1mHhcC6Xq6vdwzSz9nY+bxUrc0da3cvXbN+R1q5/VN88J88O3BH3f+xr8UbPj1S9FNZmT38Uoyfu/9jX4vE//WDpHzjtfE52uX3tmXj8Tz5Y/mckSsvMv/Uz8l9i4pkvHvwZAQAAAOgg3i8pr+73GTuAJfcPSvx91w7T9b83ltw/yDnpOoLxOuRyuSgUCnueGxwcrLm9dDpd9vl8Pp94wNvM2tv5vNXj2YE74lMf+Up8+8zFnee2l6/Zb3v5mv9wYSK+/Oe/0lGDkPVUX3zqI1+J9Z7+mgarERFbPb2xHv3x6Y88Eo//yQej9vtBW09/cSM++eyX41ef/XJ885Y746mzpbsWX+/70Ti98cPSXYvXnogPvPpU5961CAAAALCL90v28j7jW7aX3L//Y1+L9eivauZ479Z69G+td8yS+953PZrfmyi75H7d56RDJvNtc046n2C8Dk8++eSB586cOVNXm0NDQ5HL5fY8l8/n62qznGbW3s7nrVaWr3nLIxcux7fPXKzoPBxls6c/njnzs/HIhcvxyYRqO3Fnz5buHiuz3H4qIi6++lRcfPWp6to8darULi3pC1/4Qrz22mtx8803x2c/+9lmlwMA0BDGPAA0Ss3vl3QQ7zMe1Kwl91ttzON918P5vTnIOTnIOekOgvE6LC8vH3guk8nU1Wa5gPiJJ56oq81ymll7O5+3Wli+5i3FYsTcz/xGom3O3/GZ+NXi37fn3cDnz5eWVCmzf0nN7F/S0r7whS/Eiy++GOfOnWuJfzABADSCMQ8ANIb3GQ/XjCX3W2nM433Xw/m9Ocg5Ocg56R6C8TqUm5F82LLelSoXEO9fdjwJzay9nc9btSxfs9fT105H/m0/nVh7xVRPrKRvi29eezYuHv/y1nT+vCAbAAAAgCN5n/F43bzkvvddy/N7c5BzcpBz0l0E43UoF/DWuyR4uYD4+vXrdbVZTjNrb+fzVi3L1+z11Ms/FqniVt3nY7dUcSueeuVH23qABgAAAMCbjth6rmYdsPWc9xkr141L7nvftTy/Nwc5Jwc5J91FMF6HRuxhfcsttxx47qRmjNer0trb+bxVw/I1B11dOxV9Wxux3ntTYm32bW3E1eunE2sPAAAAgCay9dwB3mfkON53PcjvzUHOyUHOSfcRjCes3iXB6z2+mX3Xc3w7n7fDWL7moBsbPVFMJXs5KEbE6xvJ3QkJAAAAQJPZem4P7zNyHO+7HuT35iDn5CDnpPsIxmt0krORk14SvJm1t+J5e/rpp6tq9/z583G+goG55WsOOtW3FaliMdE2UxFxum8r0TYBAAAAoFV4n5HjeN/1IL83BzknBzXznKyursbq6mrF7VabZVFeqlhM+K9llygUCjEwMHDg+XpP5+LiYoyPj+95Lp1Ox9raWl3t7tbM2lvhvP3lX/5lfOhDH6q5rx//8R+Pm2+++djXvfbft+Lv15O/o+7H+rfi5n/Unnfq/fCHm/H9f+hNvN23/chm/OiPJt8uJO173/tebG1tRU9PT7zrXe9qdjlAh3vjjTfilVde2Xn89re/PW66Kbll9QAOY8wDnCRjHrqB9xnLWF+PePnl5Nt9xzsi+vsremkrjXm873qQ35uDnJODmnlOXnvttfjBD35Qcx9f//rX4xd+4RdqPr5bmTFeo6RncR/lzJkzibbXzNpb4bydP38+UqlUzWH8D37wg7r+WNXrBxHxg+83rfuWtPbDiATvHYGG29raihdffLHZZQBdZvcbxgAnwZgHaAZjHqic9xnLqCFs7+Qxj/ddD/J7c5BzclCjz0kqlapoZWMOEozX6CSXBE9aM2tvhfN2/vz5OH36dLz++us1heOVzhgHAAAAAACA/WqdMZ5KpeL06dOC8RoJxmuUTqfLPl8oFA79XNJ9Jd3eSdTeKuft7//+76vev2FbpXuMAwAAAAAAwH4yquYQjNco6eXNT7KvZtbeSufNHw8AAAAAAABOmoyqOZLfUb7LneQe2klrZu3tfN4AAAAAAACA1iYYr9FRS4LXo1xAnMlk6mpzv0prLxQKkc/nK263ktpP8rydPXu2rjZrVe1565S+AaBdtfP107gDAKhUO1+7jXkAgEq187W728Y8233WmxFWQzCesEbMfB4eHk68zXKy2WyMj4/H4OBgpFKpGBgY2Pn/VCoVw8PDMTs7W9UPaKW113venn322QPPPfroo3XVXqlGnLd26BsA2lU7Xz+NO96yuLgYg4ODMTk5eSL9AUC7abVrdzW6acxTKBRicXExxsfHY3h4eE9f232Pj4/H/Px8277JDwCNZMzTPn0vLi7G5ORkDAwM7Olz+/H2uGdxcTGxPg8oUrNMJlOMiD0fCwsLdbU5MzNzoM2lpaWEKn5Ludqr+Ziamqq59iTP28LCQjGdTtddu74BoPO18/XTuOMtc3Nze+oZGRlpWF8A0I5a7dpdjW4a86ytrRUnJiaqfk9uZGSkuLy8nMjXDADtzJinffqupc90Ol2cmZlJ5GveTTBeh5GRkQPfqHq/SeUGxCsrKwlV/JZytW//cC8vLxfX1taKxWKxuLKyUpybmysbZg8NDe28rprakzhva2trxbGxsSN/af7Tf/pPFddeb9/1nLd26RsA2lU7Xz+NO96qZWZmpuw/ogTjAFDSStfudqq9GX3Pzc1V9cZwI96gBoB2ZcxTW+3N6vuwPLLSj0wmk+j3SzBeh3JB8MTERF1tlgt7G6Fc7f/8n//zqo8ZGhqquvYkztvuX8pMJlP8+Mc/fmTfx9VeT9/H/UJ2St8A0K7a+frZ7eOO5eXlY2dSCcYBoKQVrt216qYxz9TUVF1vDhsHAdDtjHnaY8yztrZW9+rV1dRbKcF4Hcrd3VnvgHRoaOhEBrj7+6m0r3Lh93aoXWnt9Z633TWk0+ni2tpaRX0fVXs9fVd7XDv2DQDtqp2vn9067lhbWyt7d3ImkzFjHAAOYczTHmOectsQ7v5Ip9OHjnkO+/AeDwDdxJinPcY8hx27ffzS0tLOitNra2vFpaWlY1eJHhsbq+prPoxgvA5LS0tlB7D12D/wbcT6+YcNwiupfW1treyxKysrFddez3nbX/v23uSV9H1U7fX0XYl27hsA2lU7Xz+7cdyxsLBQdnmtkZGR4tLSUrFYLH+3smAcgG5nzNM+Y57D3lw+7LilpaWK9iHfHisBQCcz5mmfMU+xWFveedxe5MvLyxXXfhjBeJ3KfWPqWd+/Ed/k4/qotvZySz7943/8j6uqvZa+99eeyWQO/ZoO67tc7ZXcZXJY39Vox74BoF218/WzG8cdKysrZY/Z/w+tcm0LxgHoZsY87TXm2b3iYTqdrvgN7ZWVlSOXIrVtHgCdzpinvcY8u/vNZDJVZZ1ra2uHhuNJzPIXjNep3KyWau622G3/TOp6Z5+Xc9w+RpXUfly4XknttZy3/bVv311SzXmr9e6Ww/quRjv2DQDtqp2vn9067tgex01NTR16w6RgHAD2MuZprzHP7jd5a5kMc1Q47j0eADqZMU97jXkWFhbqOr+7j9/9UUuwv19PUJfx8fEDzz322GM1tbWwsLDn8cTERFXH5/P5Iz9fKBRidnb2yNdUUns6nY6hoaEjX3Nc7dWet3K1j42NRUR15+2w2hcXF2vquxrt1jcAtKt2vn5287hjeXk51tbWYmZmJtLpdNX9AkC3afa1ux7dOuYpFAo7/R333lo5S0tLh34um81W3R4AtANjnvYb82yPWcbGxiKTyVTd59jYWIyMjBx4/vr161W3tZ9gvE733nvvgedq/SX66le/uufxgw8+WNFx2Ww2BgYGYnBwMFKpVExOTh76ut1uvvnmA6+ptPZyP5C7HVd7tedtf+3pdHrnl6na81au9mr+YbG772q1U98A0K7a+frZzeOOWt4cBoBu1uxrdz26ccyze0JLpe/57ZfJZA6dEOI9HgA6lTFPSbuMeSIinnzyyYiIuO+++2rqLyLKZp3bNxnWQzBep3Q6XfYOi/n5+arayWaze76hExMTFc2UyeVyMTo6uufY+fn5imZkf/CDH6y59tHR0UM/V0nt1Z63/bXfddddEVHbeStX+1F31R7Wdy3aqW8AaFftfP007gAAKtXO1+5uHPNsB+OZTKauGwIPmxCTxBvFANCKjHlK2mXME1HKLiNqm6G+rVyIn8SkCsF4AmZmZg48Nz09XVUbu1+fTqfLtlnOQw89VPb5xcXFA0ur7/8hHRoaqrn2w36BfvzHf7zi2qvpu1zt+19f6Xk7rPbtX9RK+65FO/UNAO2qna+fxh0AQKXa+drdjWOe7ffpjluF8TiH1ZvE0qIA0IqMeUraacwzNDQUU1NTNfcXEWUnwdY64303wXgCMpnMgUC2UCiUnbVdzuzs7J4fnitXrlS8r+JR+4rvbjOXyx24c3RwcLDm2g+r77d/+7crrr3Svg+rvdbzdthryp3Lw/quVbv0DQDtqp2vn8YdAECl2vna3c1jnqGhoYrfL6y23zNnztTdLgC0mmZfu+vRrWOeTCYTy8vLFU+iPUy51XAOWzmnGoLxhExNTR24+2FxcfHYwe7s7OyeWc9zc3NV3bVx1NIHu9vZXs9/t+0Bc621v/vd7664zsNU0ne52r/+9a/Xdd7KvbbcL/BR561W7dA3ALSrdr5+GncAAJVq52t3t455JiYmYnl5ue4Z4xHla05iBhUAtBpjnr3aYcyTlP1fw9DQUCLjqL66W2DHzMxM3HLLLXsC28XFxRgYGIiJiYm4++67I5PJxPXr1yOXy8Xc3NzOD006nY6FhYWqv6kzMzPx1a9+9cCdE1NTU3sGxMvLyweO3f35Wmp/6aWXDrT5xBNPVFV/JX2XW4rhK1/5SkTUft7K/QEoV/tx560W7dA3ALSrdr5+GncAAJVq52u3MU/9yi2bXs8sMABoVe187Tbmqc/c3Nyexw8//HAi7QrGEzY1NRVjY2MxPj6+E+gWCoWYnZ099JixsbGYmZmp6YcynU7H8vJyTE5ORjabjUwmE9PT0zExMbHndeXu2ti/9EEtte9XbmmDSpz0eSt3TLnaKzlvndg3ALSrdr5+GncAAJVq52u3MU/9yrWfxAwqAGg17XztNuap3eLi4p5JszMzM3Xtkb6bYLwBttfPz+fzMTc3F7lcLvL5fOTz+Uin05HJZOLMmTMxOjoaExMTifwwLi0tHfmacr8Ehy27VGntL774Yvz7f//v9xxf7o7Var6Ow/re7zvf+U785E/+ZM19lTvn5Wqv9Lx1Wt8A0K7a+fpp3AEAVKqdr93GPPUpt7JiOp1O7M1iAGgl7XztNuapTaFQiMuXL+88npiYOLAlcz0E4w2UyWTq3lw+KdWu819J7eVmcydxd8j+vlOp1IHXvO1tb6urj1tuueXAc5XeVVOvdugbANpVO18/jTsAgEq187XbmKc+jz322IHnWuX9RwBIWjtfu415anP58uWddqemphIf5wjGu1i9M9XrPb6ZfddzfLf2DQDtqp2vn8YdAECl2vnabcxTufn5+T2PM5nMgS0VAaCTtdu1O8m+O3nMk8/n92y3PDc315AxjmC8C5zkzJykl01oZu3d2jcAtKt2vn4adwAAlWrna7cxT30WFxcPfB1zc3MN6QsAmq2dr93GPIfLZrN79ivP5XLx2GOPxeLi4s5zY2NjcddddyVS436CcWpW734EzdTM2ru1bwBoV+18/TTuAAAq1c7X7m4Z80xPT+95PDExESMjIyfWPwB0AmOe5vWdzWZjdHT02NctLi7uBOVjY2Px4IMPxtDQUN39R0T0JNIKLe0kZ+Yk/UvZzNq7tW8AaFftfP007gAAKtXO125jntrNzs7u2S80k8mYLQ5AR2vna7cxT3lLS0tV97G4uBjDw8MxOjqayN7pgvEucJLLJiStmbV3a98A0K7a+fpp3AEAVKqdr93GPLXJ5/N7Zoun0+ma3lgGgHbSztduY57ytvcPn5iYiKWlpVhZWYlisRjFYjFWVlZibm7u0NVwstlsDA8P77RRK8F4F0in02Wfb8Qvx2F9Jd3eSdTerX0DQLtq5+uncQcAUKl2vnYb89RmfHx8z+MrV67s2ZsTADpRO1+7jXnKm5mZiWKxuBOA7x7PZDKZncB8aWmpbNuFQiEuXbpU19ciGO8CJ7lkZdJ9NbP2bu0bANpVO18/jTsAgEq187XbmKd609PTe2ZGLSwsJLbHJgC0sna9djeivWr6auXzVukYZmRkJJaXl8t+rlAoxOXLl6vqdzfBeBc7yX0GktbM2ru1bwBoV+18/TTuAAAq1c7XbmOe8hYXF2N2dnbn8dzcXIyNjTWxIgBovla+dh/HmKdymUwm5ubmyn5ucXGx5lnjgvEu0KhlE8r9EiW9jFMza+/WvgGgXbXz9dO4AwCoVDtfu415KpfL5fYsoT4zMxMTExN1twsA7aLdrt27GfMkY2Ji4tCv56tf/WpNbQrGu1gj7g4ZHh5OvM1ymll7t/YNAO2qna+fxh0AQKXa+dptzLNXPp+PS5cu7TyempqKqampessCgI7QitfuShnzVO+wGwMPW2r9OILxLlHuro167w4pd3wj7g5pZu3d2jcAtKt2vn4adwAAlWrna7cxz/HtjY6O7rQ7MTERMzMzNbcHAO2sHa7dhzHmScbo6GjZ5/P5fE3tCca7RLkfzlp/aLatrKxU1E+9mll7t/YNAO2qna+fxh0AQKXa+dptzHO0S5cu7dQ0NjZ26N6aANAN2uHafRhjnmQc1sdhS6wfRzDeJcr94JT7Ia7GSe0n0Mzau7VvAGhX7Xz9NO4AACrVztduY57DjY6ORi6Xi4hSKL6wsFBXbQDQ7lr92n0UY55knDlzpqrnjyMY7xLl1vmv9+6Q/cePjIzU1d5hmll7t/YNAO2qna+fxh0AQKXa+dptzFPe6OhoZLPZnTaE4gDQ2tfu4xjzNFat+5sLxrtEubs2nnzyybra3P9LcNg6//VqZu3d2jcAtKt2vn4adwAAlWrna7cxz0Hj4+M7ofjQ0FAsLS3VVRMAdIpWvXZXolvHPPUG8PuVm6keEXHvvffW1J5gvEuUu3OjUChEoVCoqb1yxzbq7pBm1t6tfQNAu2rn66dxBwBQqXa+dhvz7DU5ORmLi4sRUQrFl5eXa6oFADpRK167K9WNY56BgYGaZ3IfplzQPjIyYo9xjlfuh3T7btRq7b+zJJ1Ox9DQUE1tVaKZtXdr3wDQrtr5+mncAQBUqp2v3cY8JdPT0zE/Px8RpZldV65cqakOAOhkrXTtrla3jXlGRkaiUCjs3PSXhHIr6czMzNTcnmC8i4yPjx947rHHHquprf37HE1MTFR1fLVLKTSz9m7tGwDaVStdP415KusbAKheK127jXkq63u32dnZmJ2djYhSKL68vFzzzCcA6GStcu2OMOY5ru/77rsvIiIeeuihmvopZ3/IPjY2VtfNDKlisVistyjaQ6FQiIGBgQPP1/IjMDAwsGfZhLW1tYoG79lsNsbHx3eOnZiYiLm5uWOPa2bt3do3ALSrVrh+GvM0ZtwxPT298wbytpGREftwAtCVWuHabcxT23mbn5+PycnJiCjNuFpeXi67FygA0BrXbmOeyvre3efS0lLdy9Rns9k9e5mn0+l4/vnn63qPyYzxLpJOp2NsbOzA89tLNlUqm83u+QWYmJio6Icwl8vF6OjonmPn5+fL3rWyXzNr79a+AaBdNfv6aczTuHFHub2wrl+/nkjbANBumn3tNuap7bwtLi4eGYpv7+FZKBQin8/vfORyucjlcpHNZiObzcbi4mIsLi7G/Px8zM/Px+zsbExPT8f09HRVXwcAtLpmX7uNeSrve/cS67tvJKjV9phpu+1EVtgp0lVWVlaKEbHnI51OV9XG0NDQnmPX1tYqOm5sbOxA39sfKysrLV17t/YNAO3KmKczxx3lzm0mk0msfQBoN8Y87TXmWVhYOPScJfkBAJ3GmKd9xjxTU1M7rx8aGqqqr912n/d0Ol3Rua6EGeNdJpPJHNiUvlAoVHRnS0Rp/6NcLrfz+MqVKxXfnXHU3gu72zxMM2vv1r4BoF0Z83TeuKNQKBzYVyoidmZQAUA3MuZpnzHP9hKsAED1jHnaZ8wzODi48/+5XC4GBwdr2pt9+z2gTCaT7LYzicTrtJ3dd2xsf4yNjR15zMzMzJ7Xz83NVdXnxMREXXfVNLP2bu8bANqVMU/7jztWVlaKCwsLxUwmc+h5TafTxbm5ueLy8rKVcQDoSsY8rT3mWV5ePvRcNeIDADqVMU9rj3mKxcPHPWNjY8Xl5eVDj1tbWyvOzc0V0+n0zjETExNVfZ2VSBWLNeyyTkfY3ntot3Q6HRMTE3H33XdHJpOJ69evRy6Xi7m5uZ07OtLpdCwsLMTIyEhV/RUKhXjf+953YE+BqampA3estFrt+gaA9mXMU5tm9T0wMFD3HlS7611bW0ukLQBodcY8tTmJvpMc31TC270AdDJjntqcZN+pVOrQz6XT6bjrrrt2ZoBfv379wGqAQ0ND8fDDD+/sV56oxKN22srKysqe/QGO+xgbG6trHf+VlZXiyMhIMaK0H2Q9M4lOunZ9A0D7MuZpn74r7avSDwDoJsY8rdl3PWOZdDpdTKfTxUwms/P/uz/KHWMFHQA6nTFPa/c9MzNTVT+7+1taWkrkaz2MGeNERGmPhLm5ucjlcpHP5yOfz0c6nY5MJhNnzpyJ0dHRmJiYaMm9qZtZe7f2DQDtqp2vn8YdAECl2vnabcwDAFSqna/d3TLmyWazsbCwEPl8fmd2eKFQiEwms/MxPDwc995774l8nwTjAAAAAAAAAHS0nmYXAAAAAAAAAACNJBgHAAAAAAAAoKMJxgEAAAAAAADoaIJxAAAAAAAAADqaYBwAAAAAAACAjiYYBwAAAAAAAKCjCcYBAAAAAAAA6GiCcQAAAAAAAAA6mmAcAAAAAAAAgI4mGAcAAAAAAACgownGAQAAAAAAAOhognEAAAAAAAAAOppgHAAAAAAAAICOJhgHAAAAAAAAoKMJxgEAAAAAAADoaIJxAAAAAAAAADqaYBwAAAAAAACAjiYYBwAAAAAAAKCjCcYBAAAAAAAA6GiCcQAAAAAAAAA6mmAcAAAAoIPkcrmYnJyM4eHhSKVSMTw8HJOTk1EoFJpdGgAAQNOkisVisdlFAAAAAFC/6enpmJ2dPfTzCwsLMTY2doIVAQAAtAbBOAAAAEAH2B2Kj4yMxPj4eGQymcjlcjE3Nxf5fD4iIpaWlmJkZKSZpQIAAJw4wTgAAABAm8vlcjE8PBwREVNTUzEzM3PgNaOjo5HNZiOdTsfa2tpJlwgAANBU9hgHAAAAaHOPPfZYRERkMpmyoXhExNzcXEREFAqFyGazJ1YbAABAKxCMAwAAALS5XC4XERFDQ0OHviaTyUQ6nd7zegAAgG4hGAcAAABoc9evX4+IiDNnzhz5uu3Pv/rqqw2vCQAAoJUIxgEAAAASVigUIp/P73w02sjISEREPPnkk0e+bruWu+++u+E1AQAAtBLBOAAAAOySy+VicHAwCoVCs0uhjY2Pj8fg4ODOR6ONjo5GROnn97D9w6enp3f+fztIT8ri4mIMDw/7vQEAAFqWYBwAAADelM1mY3h4OPL5fDz00EPNLoc2lc/n94TTU1NTDe9zZGQkxsbGIqIUks/OzsZ73vOeSKVS8U/+yT+J8fHxmJ2djYiIubm5nb3GkzI9PR25XE44DgAAtKxUsVgsNrsIAAAAaLbFxcUYHx+PiIhMJhMrKytNroh2NTk5GfPz8zuP19bWEg+iyykUCnHp0qXI5XKHvmZiYiLm5uYS73s7FI8o/f4sLy+fyNcMAABQKTPGAQAA6Hq7Q/F0Oh1LS0tNroh2VSgU9oTiY2NjJxYQp9PpWF5ejpmZmejr69vzubNnz8bS0lJDQvGIiKGhoZ228/m8meMAAEDLEYwDAADQ1bLZ7E4oHhGxsLAQmUymiRXRzvYvwf/ggw+eeA0TExOxsbGx57mbb7458X3Fy/U7MTEREcJxAACg9QjGAQAA6Fq5XC5GR0d3Hk9NTTU8PKSz7Z4tPjQ0FENDQ02tYdv+fc8bZW5ubudrzufzcenSpYb3CQAAUAnBOAAAAF1pez/mbUNDQzEzM9PEiqhVPp9vdgkRUQqkd8+QbsZs8Yg4dLn0k/r5XlhY2Pn/XC63Z0UGAACAZhGMAwAA0JUuXbq0J8TcHebRHmZnZ2NgYCCGh4ebXUpE7A2e0+l0jI2NnXgN2Wz20BsFjvpckjKZTExNTe08XlxcLDuLHQAA4CQJxgEAAOg68/Pzkcvldh5PTU3ZV7xN5HK5mJycjIGBgZieno5CoRBnzpxpdlkHQudmzRY/blb4YbPJG1HH7t+pyclJ+40DAABNlSoWi8VmFwEAAAAnpVAoxMDAwJ7n1tbWIp1ON6cgqpJKpQ48NzIyEktLS02o5i2jo6N79vBuxs9UPp+PwcHBiCjN2i43OzydTsfa2tqJ1DM/Px+Tk5M7j1vh+wQAAHQvM8YBAADoKpcvX97zeGpqSijeRsp9r5r9/cvn83tC8YmJiabUtHu2+MzMTNml3AuFwoktaz4xMbFn1ng2m43FxcUT6RsAAGA/wTgAAABdI5fLHQjmmrXkNbUpt2x6s5fB3798+fT09InXsDvw3t7ffPds7d2OW249SfvPxf4bUwAAAE6KYBwAAICu8dBDD+15PDIy0vTZxtTvlltuaVrf+2dgj4yMNCWo313D9s0eh9WSz+cjl8udSF333nvvnseFQsGscQAAoCkE4wAAAHSFcoHcYTNqaV2ttpT6/mXJmzFbPGLvTR8TExM7/39YPftvEmmUdDodIyMjTekbAABgN8E4AAAAXaFcGFduD2baT7nl1U/K7p+rTCZzIAQ+CYuLi1EoFCKi9DO9+0aB3SH5Ycc02v4bUHK53J492QEAAE6CYBwAAIDE5fP5mJ2djdHR0RgYGIhUKhUDAwMxODgYk5OTJ7aM8277Z/Y2I8Bstu0ltLPZbORyucjn8w3v87jwdbumk6glafvD5VaYLb69jPpuh4XjJzVzu9zv2tzc3In0DQAAsE0wDgAAQGJyuVyMjo7G4OBgTE9PRzab3QkOC4VC5PP5mJ+fj+Hh4RgfHz+xunbXsW1oaCiRtrf3mB4dHY3h4eEja5icnNw5P9s3C2yfi0bM4C0UCjE7OxvDw8ORSqVicHAwhoeHd2rdrmN0dDTRfZ8XFxdjfHw8UqlUXL58uexrpqend26W2K5lYGCgrQLy3cFyOp0+NIBupFwut3OjydDQUNmf68MC+/03izRKOp0+sNe5fcYBAICT1tfsAgAAAGh/hUIhLl++vBN2jY2Nxd133x3pdDoKhUIsLS0dWDp5cXExhoeHY3l5ueH1lZudOjo6WnN7+Xw+stlsLCws7Pm69od/EaVzc+nSpbKz5AuFwk6wuX3uJiYmYmZmpq59swuFQjz00EMxOztb0euz2Wxks9kYGhqKK1euVNV3oVCIJ598MnK5XDzxxBPHBp75fD5GR0fLBuC13hjQjD3GdwfSEYfPym6042aLR7y1xPv+38FCoRCLi4snsqXA0NDQge/5SfUNAAAQEZEqFovFZhcBAABA+8rn8zE8PByFQiHGxsbi4YcfLhtUbs8i3m9qaipmZmYaWuPAwMCB0HVtba3iQDWfz8fMzMxOAHyYTCYTKysre47bPjfVWlhYqCk0nJ+fj+np6ZpD5v1fQ739jI2NxcLCQkSUgtj3ve99Rx5z1PflsD7HxsYik8nsPH/9+vUoFApx/fr1na9pu4akbM/yr6TuRikUCjEwMBARpZsD1tbWDn3tYb9/Q0NDJ3Jzyvz8/IG9xnf/bAAAADSaGeMAAADULJvN7sy8HhkZOTLkGhsbi+Xl5QPLjc/OzsaDDz7YsFAxn88fCFLT6XRV/WWz2aqXnc7lcnHp0qWaA+rx8fGqbhrI5/MxPj6+Z1ntmZmZuOuuu3a+1t2zu+fm5srO2s7n8zE9PX1sv5WE5/tVcpPA/u/L9uz3+fn5Q489bpb6XXfdVUWVx9ueab1tbGysKbPWd88WP27G+naN+8/h9sz3pLYWOEy578H+GewAAACNZI9xAAAAarI7FI+IimZ+Dg0NxcjIyIHnG7nXcbnwrVwNR7n33ntjaWkplpaWYmFhIaampo7tczsEzmQyMTU1FUtLS7GyshJra2uxsrISS0tLMTU1VXb59W2zs7MVL4c+Nze3E4pnMplYXl6OkZGRPYFtOp2OkZGRmJqaipWVlUPD70r6nJmZibW1tSgWi1EsFmNpaenI1x+2fPpRZmdnY2BgIGZnZ+vaf31wcLDmY8vZHUhHHL6EeaPt/r2ppIbDXlNuq4GklQveC4VCXd9XAACAalhKHQAAgKrtXxJ7Zmbm2LB42/5APaIUVB8XrNZq/5LXEcks316u3UwmEzMzMzE+Ph7pdDpmZmYq2nv6uGXJl5aWjg3zp6endwLtapZhn52djenp6QPP17KU+/Dw8IGl5sfGxuLMmTMxPz+/c07uvffeSKfTkcvl4qGHHto5j/uXA5+dnY2lpaVIp9Nx5syZSKfTZUP77T3tD7O91HpSUqnUzv838mf3KLuXJq90SfLdS6/vdxJLwQ8ODh64OaLWLQMAAACqJRgHAACgaqOjozszsY/b27ic3cFirW1UqlxYOzc3V1FgfZRyeyZvS6fTsby8XFUYm8/nD51VXcm+39vBeKV7hO9WLrCcmJioeibx5OTkobP/h4aG4sqVK2XD1+3aK9nvutx+8ZXcOJCU/d/3k+x7t93fs+Xl5YqXQi93Q0dEdTe31Gr3342T7BcAACDCUuoAAABUaXZ2dk+4VUvAXG4f6UY5LGiu15kzZ8o+X0sovl3TYTOP8/n8scvN33LLLRERZWd/H6fcMU8++WTV7Rw14/iwUDyiFI6OjIwkOqu7UXavNJDJZJoSimez2Z2f60wmU9X+4Ictp75/efhGKPf9rWWvegAAgFoIxgEAAKjK/gDtsFnTRzmpAPSwPYwPC7WTMDMzU/PXt70UeznHzd6empqKtbW1mm5UKBfuVrsf+FFmZmaOXaZ7e//2VrY7kI6o7SaEJOz+Gam2hqGhoUP3+y43kzxJ5X4GarkBAwAAoBaCcQAAACo2Ozu7J2jOZDI1hcCNDKZ3u379etnnG7mXcr1LtE9NTZWtL5fLHTuzvtavq9z3MMlZ/PWek1ax/6aFZnxd+Xx+zzYGtdRw2M0s1S6dX63tVQ12a+RqEQAAALsJxgEAAKhIoVA4MDu11mWk9wfWjZpBftKhW1KB+7333lv2+UbOrm3UzQLpdLqhNyKclFwut2cLgWbti707nK81mJ+YmCj7Pdk/Iz5p5fo87OYVAACApAnGAQAAqEi5PYhHR0dramt/YH3Se0s3asZ6Uu0edl6TCvpzuVzMz8/H5ORkjI6OxsDAQNm2k+jvrrvuqruNVrD/5/+wvbobbfde87VsY7DtsFD9sKX8AQAA2l1fswsAAACgPewO5LaV26u4EvtniTZqRnG7zkY97LzW8vUUCoX46le/GsvLyw2fEVxOJ8wW37//9tjYWFO+rtnZ2T2PBwcHE+9jfn6+4Uuq72YpdQAA4KQIxgEAADhWNps9EGCl0+maZ3qf1Izxw2ZwX79+vaUD28POR6XnqVAoxPz8fDz22GORy+UOfd3Q0FDcddddMTw8HNPT00LKQ7TKbPGTCqzn5+cbsn96uZ+vVv49BAAAOotgHAAAgGMtLCwceK7WJbLLzVi+7777amrrOIeFbu0aAFcSjE9PTx+YWbxtbGwsRkdHY2Rk5EBbMzMzbXteGm33aglDQ0M1r5RQj8XFxZ3fnXQ6nUg4/+qrr5b9WZmZmWlIMP7qq68eeK5R2xoAAADsJxgHAADgWF/96lcPPFfrLO/9M5jT6XTDgsajZoy3o6POeS6Xi/Hx8QM3HmQymZiZmYmxsbFGl9eR5ufn99ww0KzZ4rtnrT/44IMxNTWVSLu7A/dt+Xw+stlsjIyMJNLHNjPGAQCAZuppdgEAAAC0tnLLqEfUHmg98cQTex4nHb7t1q4zxsvVd1Swnc/n49KlSwcCzomJiVhZWRGK12FmZmbn/9PpdFPOZS6X23NDSZKzuaenp8s+v/vrTkq5G1LMGAcAAE6KYBwAAIAjlVtGPSLilltuqam9bDa753GjllE/SqvPGC+33Pzk5OShrx8dHT0Qpo+MjJzYntSdKpvN7vletMLe4hMTE4nOsr733nvLPr//a0+CGeMAAEAzCcYBAAA40pNPPln2+aSWUm/0DNxyy7S3+ozx/TcPpNPpQ2fWl1sKO+LwGxqo3P5Z043Yd/s4hUJhzx7nR90gUYujZsEnfWNFuRtSav07AgAAUC3BOAAAAEfaH2Rvq2Wm5+Li4p7HSe2TfJS77rrrwHOvvvpqw/utx9LS0p7HRwWy5cLLsbExM3HrtL3P9rakZ2pXancoPjQ0VPZGj3odNhN+d99JKHdDyujoaKJ9AAAAHEYwDgAAwKEOC8Ujapt1vT/EPYmlqYeHhw88l/QS0UkqFAp7Atl0On3keSo3o//uu+9uSG3dZP9s8cP24m60hx56aOf/k54tvm1oaKjszO39s9XrVe73rtyNKwAAAI0gGAcAAOBQ+5f03q3acHl/4Ds1NXUiM3DLBW9HBf7NtjsIjSgFtEedp3I3KNSyPHWr77t+lKSXxt8fCI+MjDRlye/FxcU9X1sjl3I/LPjff4NArcr9vUin01Y2AAAAToxgHAAAgEM98cQTh35uZWWlqrZ2B43HzYJOUrmlp/P5fEvuM57L5WJ2dnbncSaTqSkMPer7Vs7o6GhLno9KJR3q758l3QqzxQ/bBzwp9957b9nn9y8pX6tyN6OMjIzU3S4AAEClBOMAAAAc6qiZ1eWW8D5MoVDYE/ItLCyc6EzRcgFcNfVXqp4QsVAoxPj4+M7jdDp9YK/xcsqdx2pqGB8fP/T1SQTOJxG4J93H7p/VTCbTlAA3l8vt+f277777GtpfOp0+NHxPYtZ4uZ9lS/4DAAAnSTAOAADAoY5aLn1/cHeU6enpnfByamrqxIPG3YHztkYtpz46Olr1vsyFQiEuXbq0c76Hhobi+eefr2j57sOWij+uhlwuF4ODg5HNZmN5eTmRGxVOIgQvd072711fj/3Llzdrtvj+fk/id+awPcyz2Wzdvy/lbkRp5NLwAAAA+wnGAQAAKKuSPcQrCQ0XFxd3QtqJiYnE9iyuRrlloiuZjV2rycnJGB0dregcZrPZeN/73rcTPM7NzVUVVJcL/bdr2L0s+7Z8Ph/j4+MxPDwcmUwmnn/++RgaGiobalcbdJf7epOemV8uGN/+mnbXm8vldr7OauyeLZ5Op5sS3s7Pzx+YxX8SKyyUu8li22E/Z5XaH6wPDQ3ZXxwAADhRgnEAAADK2h9yjo2NHQiystnskftTT09P7wRqMzMzic7srUY6nT6w13gjllLfLZvNxuDgYAwPD8fs7GwsLi7uzLLPZrMxOzsbg4ODO+dvZGQk1tbWqg5iJyYmyu6jHlE6/4ODgzE+Ph7j4+MxODgYg4ODsbi4GDMzM7G0tHRkOLk7JD5KoVAoG+Zuf25ycjKxfd1HR0fLPr+4uBgDAwORSqUilUrF8PBwLC4uxpkzZypue/8qCA8++GDd9VYjn8/H9PR02Znbo6Ojkc1mGzIrv1AoRC6Xi8uXLx9Z2+joaE0zx8sdc9jsdAAAgEZJFYvFYrOLAAAAoPXMz8/vCa+WlpYO7IO9LZ1Ox7333rszO3dlZSUWFxcjn89HOp2OhYWFpuzTvNvi4uKB2ldWViparrzS9mqRTqfj4YcfPnR/50rkcrmKZ0an0+m4cuXKnjC9UCjEwMDAscft/j5OTk7GV7/61ZqC2nQ6HXfddVfNs/YHBwcrmo0/NDQUy8vLFbc7Pj4ei4uLO4/X1tYaPqu5UCjE+973vqrPY7nvYzVmZ2fjoYceqjloT6fTsba2VnFf+1eXOIlzCwAAsJsZ4wAAAJS1P1A8c+ZMjI2NxcLCwoHXbs8Ynpyc3FnC+/r16zEzMxNra2tND8UjSjPe94fgSc9gT6fTVX2tY2Nj8fzzz9cVike8FQAfF/KPjIzsLJ2+2/Xr18u+Pp1O73zsD1ArmQG++/jtj4jSz0slwfZhFhYWjv1aM5lMXLlypeI28/n8nlB8YmLixILbo87jUeewHq+++mpFbZTru9r+9/+elVt9AgAAoNHMGAcAAKCs7aWbt+2e4bkdhD/22GM7AWk6nY5MJhN33XVXjI+Pt0QYvt/+WfCZTCZWVlZqaqvcjPHt9gqFQjz00EORy+XiySef3AkRd5+jycnJmmf7HmV+fj4WFhb29JvJZGJ6erop+2U30vz8fMzNze0J6TOZTAwNDcXDDz9cVfg6PT29Z0/2elYT4C35fD4GBwf3POfcAgAAzSAYBwAAoKzh4eE9ewN3yj8fBwYG9sx2rTWkOyoYp/2kUqmd/x8ZGal5mXf22r+M+mGrTgAAADSapdQBAAAoq56lrlvZgw8+uOfxzMxMkyqhVczPz+95vH8/bGr30EMP7Xns9w0AAGgWwTgAAABl7Z5V3Un7AU9NTe2ZIT4/P1/3fs20t91hbSaTacltANrR4uLint+tiYkJS6gDAABNIxgHAADggE6dLb5tbm5uz+P9s1rpHouLi3t+3s0WT87uc5lOp80WBwAAmkowDgAAwAH7g/EzZ840qZLGGBkZibGxsZ3Hs7OzZo13qd03RaTT6ZiYmGhiNZ1jfn5+z9+Rhx9+uKNWngAAANqPYBwAAIADuiEkXlhY2LOs8/j4eBOroRlyuVzkcrmdx0LxZBQKhT2zxScmJvbciAIAANAMfc0uAAAAgNbT6Uupb1tYWIjh4eGIiMhms7G4uCjA6zK7l9W/9957m1hJ57h8+fLOzTVDQ0MHti4AAABoBsE4AAAAB6ysrOx53KlLIA8NDcXS0lKMjo5GRCnQGxkZ6divl72GhoZiaGio2WV0lO0bTCJKfzeuXLnS5IoAAABKLKUOAADAAdevX292CSdmZGQkFhYWIqK0BLQl1aE2u39/0ul0LC8vu8kEAABoGYJxAAAADuiWpdS3jY2NxczMTESUZrzu3h8ZqMylS5eiUCjszBTPZDLNLgkAAGCHYBwAAIADtvcH7iZTU1M74fjs7Gxks9mq2+immfaw2+TkZORyuZ1Q3BL1AABAqxGMAwAAcMD+GePdEpRPTU3F3NxcRHTP1wxJuH79+s7y6UJxAACgFfU1uwAAAABaS7cHwhMTEzEyMnLsMtDlZod3+7mjey0sLEQ+n7d8OgAA0LLMGAcAAGCPcoFvty0RXkm4t7y8XPZ54TjdSigOAAC0MjPGAQAA2GP/MuqUFAqFuH79ehQKhXjyySdjfn6+7OvGx8djeno6MplMnDlzJtLp9MkWCgAAABwgGAcAAGCP3cF4Op2Ou+66q+v3DJ6eno7Z2dmKXpvNZiObze55rlgsNqIsAAAAoEKCcQAAAPaYmJiIiBCI73LLLbfsLBO9PQP8zJkzh75+e+l5y6oDAABAa0gV3bYOAAAAAAAAQAfraXYBAAAAAAAAANBIgnEAAAAAAAAAOppgHAAAAAAAAICOJhgHAAAAAAAAoKMJxgEAAAAAAADoaIJxAAAAAAAAADqaYBwAAAAAAACAjiYYBwAAAAAAAKCjCcYBAAAAAAAA6Gj/f6tTL5a9UD7XAAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<Figure size 2000x1000 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(20,10))\n",
-    "\n",
-    "ax = []\n",
-    "n = 0\n",
-    "l_tot = 1\n",
-    "c_tot = 1\n",
-    "\n",
-    "x_boundaries = 0.0, 0.003\n",
-    "x_ticks = [0, 0.001, 0.002, 0.003]\n",
-    "y_boundaries = 0, 0.2\n",
-    "y_ticks = [0, 0.05, 0.1, 0.15, 0.2]\n",
-    "\n",
-    "n += 1\n",
-    "ax.append(plt.subplot(l_tot, c_tot, n))\n",
-    "\n",
-    "for path, legend, color, symbol in zip(paths, legends, [myred, myblue], [\"s\", \"o\"]):\n",
-    "    data = path + \"density.dat\"\n",
-    "    file = open(data, \"r\")\n",
-    "    steps, dens = np.loadtxt(file).T\n",
-    "\n",
-    "    proba, density = np.histogram(dens[10:], bins=25, range=(x_boundaries))\n",
-    "    density = (density[1:]+density[:-1])/2\n",
-    "    proba = proba/np.sum(proba)\n",
-    "\n",
-    "    ax[-1].plot(density, proba, symbol, color=color, markersize=15, label=legend)\n",
-    "\n",
-    "plt.xlim(x_boundaries)\n",
-    "plt.xticks(x_ticks)\n",
-    "plt.ylim(y_boundaries)\n",
-    "plt.yticks(y_ticks)\n",
-    "\n",
-    "complete_panel(ax[-1], r'$\\rho$ (part/\\AA)', r'$p$ ($\\rho$)', legend=True)\n",
-    "\n",
-    "fig.tight_layout()\n",
-    "plt.savefig('density_300K_2kcalmol.png', bbox_inches = 'tight', pad_inches = 0.062)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "paths = [\"lammps_25part_300K_NPT/\", \"python_25part_300K_NPT/\"]\n",
-    "legends = [\"LAMMPS\", \"Python\"]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 2000x1000 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig = plt.figure(figsize=(20,10))\n",
-    "\n",
-    "ax = []\n",
-    "n = 0\n",
-    "l_tot = 1\n",
-    "c_tot = 1\n",
-    "\n",
-    "x_boundaries = 0.0047, 0.0055\n",
-    "x_ticks = [0.0047, 0.005, 0.0055]\n",
-    "y_boundaries = 0, 0.2\n",
-    "y_ticks = [0, 0.05, 0.1, 0.15, 0.2]\n",
-    "\n",
-    "n += 1\n",
-    "ax.append(plt.subplot(l_tot, c_tot, n))\n",
-    "\n",
-    "for path, legend, color, symbol in zip(paths, legends, [myred, myblue], [\"s\", \"o\"]):\n",
-    "    data = path + \"density.dat\"\n",
-    "    file = open(data, \"r\")\n",
-    "    steps, dens = np.loadtxt(file).T\n",
-    "\n",
-    "    proba, density = np.histogram(dens[10:], bins=50, range=(x_boundaries))\n",
-    "    density = (density[1:]+density[:-1])/2\n",
-    "    proba = proba/np.sum(proba)\n",
-    "\n",
-    "    ax[-1].plot(density, proba, symbol, color=color, markersize=15, label=legend)\n",
-    "\n",
-    "plt.xlim(x_boundaries)\n",
-    "plt.xticks(x_ticks)\n",
-    "plt.ylim(y_boundaries)\n",
-    "plt.yticks(y_ticks)\n",
-    "\n",
-    "complete_panel(ax[-1], r'$\\rho$ (part/\\AA)', r'$p$ ($\\rho$)', legend=True)\n",
-    "\n",
-    "fig.tight_layout()\n",
-    "plt.savefig('density_200atm_NPT.png', bbox_inches = 'tight', pad_inches = 0.062)\n",
-    "plt.show()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/benchmark/density_200atm_NPT.png b/benchmark/density_200atm_NPT.png
deleted file mode 100644
index 6d8e76b..0000000
Binary files a/benchmark/density_200atm_NPT.png and /dev/null differ
diff --git a/benchmark/density_300K_2kcalmol.png b/benchmark/density_300K_2kcalmol.png
deleted file mode 100644
index fcdffcc..0000000
Binary files a/benchmark/density_300K_2kcalmol.png and /dev/null differ
diff --git a/benchmark/energies_300K.png b/benchmark/energies_300K.png
deleted file mode 100644
index 02aa5b8..0000000
Binary files a/benchmark/energies_300K.png and /dev/null differ
diff --git a/benchmark/lammps_25part_1.7nm3_300K_NVT/input.lammps b/benchmark/lammps_25part_1.7nm3_300K_NVT/input.lammps
deleted file mode 100644
index 004979f..0000000
--- a/benchmark/lammps_25part_1.7nm3_300K_NVT/input.lammps
+++ /dev/null
@@ -1,39 +0,0 @@
-variable dump equal 500
-variable thermo equal 500
-variable maximum_steps equal 2000000
-
-# main parameters
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut 10
-boundary p p p
-
-#read_data twoparticle.data
-region myreg block -6 6 -6 6 -6 6
-create_box 1 myreg
-create_atoms 1 random 25 32141 myreg
-
-mass 1 1
-pair_coeff 1 1 0.1 1.0
-neigh_modify every 1
-
-velocity all create 300 4928459
-fix mynve all nve
-fix myber all temp/berendsen 300 300 100
-timestep 0.1
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable pressure equal press
-variable temperature equal temp
-fix myat1 all ave/time ${dump} 1 ${dump} v_Epot file Epot.dat
-fix myat2 all ave/time ${dump} 1 ${dump} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${dump} 1 ${dump} v_Etot file Etot.dat
-fix myat4 all ave/time ${dump} 1 ${dump} v_pressure file pressure.dat
-fix myat5 all ave/time ${dump} 1 ${dump} v_temperature file temperature.dat
-run ${maximum_steps}
diff --git a/benchmark/lammps_25part_300K_NPT/input.lammps b/benchmark/lammps_25part_300K_NPT/input.lammps
deleted file mode 100644
index 228bef5..0000000
--- a/benchmark/lammps_25part_300K_NPT/input.lammps
+++ /dev/null
@@ -1,44 +0,0 @@
-variable dump equal 500
-variable thermo equal 500
-variable maximum_steps equal 200000
-
-# main parameters
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut 10
-boundary p p p
-
-#read_data twoparticle.data
-region myreg block -6 6 -6 6 -6 6
-create_box 1 myreg
-create_atoms 1 random 25 14141 myreg
-
-mass 1 1
-pair_coeff 1 1 0.1 1.0
-neigh_modify every 1
-
-velocity all create 300 4928459
-fix mynve all nve
-fix mytemp all temp/berendsen 300 300 100
-fix mypress all press/berendsen iso 200 200 1000
-timestep 1
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable pressure equal press
-variable temperature equal temp
-variable volume equal vol
-variable density equal count(all)/v_volume
-fix myat1 all ave/time ${dump} 1 ${dump} v_Epot file Epot.dat
-fix myat2 all ave/time ${dump} 1 ${dump} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${dump} 1 ${dump} v_Etot file Etot.dat
-fix myat4 all ave/time ${dump} 1 ${dump} v_pressure file pressure.dat
-fix myat5 all ave/time ${dump} 1 ${dump} v_temperature file temperature.dat
-fix myat6 all ave/time ${dump} 1 ${dump} v_volume file volume.dat
-fix myat7 all ave/time ${dump} 1 ${dump} v_density file density.dat
-run ${maximum_steps}
diff --git a/benchmark/lammps_mu2_1.7nm3_300K_GCMC/input.lammps b/benchmark/lammps_mu2_1.7nm3_300K_GCMC/input.lammps
deleted file mode 100644
index 4131f7f..0000000
--- a/benchmark/lammps_mu2_1.7nm3_300K_GCMC/input.lammps
+++ /dev/null
@@ -1,34 +0,0 @@
-variable dump equal 500
-variable thermo equal 500
-variable maximum_steps equal 2000000
-
-# main parameters
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut 10
-boundary p p p
-
-#read_data twoparticle.data
-region myreg block -10 10 -10 10 -10 10
-create_box 1 myreg
-create_atoms 1 random 25 14141 myreg
-
-mass 1 1
-pair_coeff 1 1 0.1 1.0
-neigh_modify every 1
-
-
-timestep 0.1
-fix mygcmc all gcmc 1 1 0 1 29494 300 -4 0.01
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable atom atom "type==1"
-group atom dynamic all var atom
-variable n_atom equal count(atom)
-variable density equal v_n_atom/vol
-fix myat1 all ave/time ${dump} 1 ${dump} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/benchmark/pressures_300K.png b/benchmark/pressures_300K.png
deleted file mode 100644
index f301275..0000000
Binary files a/benchmark/pressures_300K.png and /dev/null differ
diff --git a/benchmark/python_25part_1.7nm3_300K_NVT/run.ipynb b/benchmark/python_25part_1.7nm3_300K_NVT/run.ipynb
deleted file mode 100644
index 499b9dd..0000000
--- a/benchmark/python_25part_1.7nm3_300K_NVT/run.ipynb
+++ /dev/null
@@ -1,456 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "step N temp epot ekin press vol\n",
-      "0 25 97.73 -1.11E-01 6.99E+00 2.18E+02 1.73E+03\n",
-      "500 25 298.48 -1.83E-01 2.14E+01 5.52E+02 1.73E+03\n",
-      "1000 25 300.61 -1.36E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "1500 25 300.05 -1.73E-01 2.15E+01 5.73E+02 1.73E+03\n",
-      "2000 25 300.12 -1.69E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "2500 25 301.49 -2.78E-01 2.16E+01 5.58E+02 1.73E+03\n",
-      "3000 25 299.6 -2.00E-01 2.14E+01 5.53E+02 1.73E+03\n",
-      "3500 25 299.44 -1.41E-01 2.14E+01 5.59E+02 1.73E+03\n",
-      "4000 25 298.81 -1.01E-01 2.14E+01 6.03E+02 1.73E+03\n",
-      "4500 25 299.21 -8.21E-02 2.14E+01 5.60E+02 1.73E+03\n",
-      "5000 25 298.67 -7.25E-02 2.14E+01 6.24E+02 1.73E+03\n",
-      "5500 25 295.94 1.27E-01 2.12E+01 7.40E+02 1.73E+03\n",
-      "6000 25 293.04 3.44E-01 2.10E+01 7.03E+02 1.73E+03\n",
-      "6500 25 303.19 -4.13E-01 2.17E+01 5.83E+02 1.73E+03\n",
-      "7000 25 300.53 -1.79E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "7500 25 300.43 -1.64E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "8000 25 297.83 9.78E-04 2.13E+01 6.59E+02 1.73E+03\n",
-      "8500 25 300.51 -2.81E-01 2.15E+01 5.67E+02 1.73E+03\n",
-      "9000 25 302.3 -2.92E-01 2.16E+01 5.57E+02 1.73E+03\n",
-      "9500 25 299.39 -1.17E-01 2.14E+01 6.03E+02 1.73E+03\n",
-      "10000 25 301.97 -3.25E-01 2.16E+01 5.57E+02 1.73E+03\n",
-      "10500 25 298.35 -4.08E-02 2.13E+01 5.61E+02 1.73E+03\n",
-      "11000 25 296.48 8.78E-02 2.12E+01 6.33E+02 1.73E+03\n",
-      "11500 25 299.58 -1.60E-01 2.14E+01 5.55E+02 1.73E+03\n",
-      "12000 25 300.99 -1.80E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "12500 25 301.09 -2.57E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "13000 25 295.95 2.20E-01 2.12E+01 6.48E+02 1.73E+03\n",
-      "13500 25 301.29 -2.26E-01 2.16E+01 5.56E+02 1.73E+03\n",
-      "14000 25 300.09 -8.66E-02 2.15E+01 5.61E+02 1.73E+03\n",
-      "14500 25 300.16 -2.54E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "15000 25 300.01 -1.14E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "15500 25 301.17 -3.40E-01 2.15E+01 5.80E+02 1.73E+03\n",
-      "16000 25 300.45 -9.37E-02 2.15E+01 5.62E+02 1.73E+03\n",
-      "16500 25 303.74 -5.25E-01 2.17E+01 5.55E+02 1.73E+03\n",
-      "17000 25 300.75 -2.85E-01 2.15E+01 5.52E+02 1.73E+03\n",
-      "17500 25 300.17 -1.54E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "18000 25 296.87 9.02E-02 2.12E+01 6.22E+02 1.73E+03\n",
-      "18500 25 299.87 -6.34E-02 2.15E+01 5.63E+02 1.73E+03\n",
-      "19000 25 299.56 -1.49E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "19500 25 302.18 -3.43E-01 2.16E+01 5.61E+02 1.73E+03\n",
-      "20000 25 297.45 -2.37E-02 2.13E+01 6.46E+02 1.73E+03\n",
-      "20500 25 300.04 -1.63E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "21000 25 301.44 -3.08E-01 2.16E+01 5.65E+02 1.73E+03\n",
-      "21500 25 301.5 -2.42E-01 2.16E+01 5.72E+02 1.73E+03\n",
-      "22000 25 302.05 -3.47E-01 2.16E+01 5.53E+02 1.73E+03\n",
-      "22500 25 299.97 -1.45E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "23000 25 301.97 -4.05E-01 2.16E+01 5.64E+02 1.73E+03\n",
-      "23500 25 300.37 -2.32E-01 2.15E+01 5.53E+02 1.73E+03\n",
-      "24000 25 301.43 -1.80E-01 2.16E+01 5.61E+02 1.73E+03\n",
-      "24500 25 300.35 -8.72E-02 2.15E+01 5.62E+02 1.73E+03\n",
-      "25000 25 301.98 -3.05E-01 2.16E+01 5.54E+02 1.73E+03\n",
-      "25500 25 299.84 -2.10E-01 2.15E+01 5.76E+02 1.73E+03\n",
-      "26000 25 299.47 -1.23E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "26500 25 299.65 -1.24E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "27000 25 300.87 -1.55E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "27500 25 300.96 -2.83E-01 2.15E+01 5.50E+02 1.73E+03\n",
-      "28000 25 302.13 -3.91E-01 2.16E+01 5.48E+02 1.73E+03\n",
-      "28500 25 302.84 -3.95E-01 2.17E+01 5.58E+02 1.73E+03\n",
-      "29000 25 301.63 -2.73E-01 2.16E+01 5.67E+02 1.73E+03\n",
-      "29500 25 300.05 -1.45E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "30000 25 301.57 -3.36E-01 2.16E+01 5.59E+02 1.73E+03\n",
-      "30500 25 301.67 -2.96E-01 2.16E+01 5.53E+02 1.73E+03\n",
-      "31000 25 298.71 -8.05E-02 2.14E+01 5.59E+02 1.73E+03\n",
-      "31500 25 301.68 -2.42E-01 2.16E+01 5.74E+02 1.73E+03\n",
-      "32000 25 300.9 -2.63E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "32500 25 300.95 -2.48E-01 2.15E+01 5.91E+02 1.73E+03\n",
-      "33000 25 300.96 -2.61E-01 2.15E+01 5.60E+02 1.73E+03\n",
-      "33500 25 301.75 -2.65E-01 2.16E+01 5.54E+02 1.73E+03\n",
-      "34000 25 305.45 -4.81E-01 2.19E+01 5.51E+02 1.73E+03\n",
-      "34500 25 299.15 -1.89E-01 2.14E+01 5.52E+02 1.73E+03\n",
-      "35000 25 297.9 6.55E-02 2.13E+01 6.66E+02 1.73E+03\n",
-      "35500 25 301.56 -2.72E-01 2.16E+01 5.86E+02 1.73E+03\n",
-      "36000 25 301.57 -2.40E-01 2.16E+01 5.71E+02 1.73E+03\n",
-      "36500 25 299.01 -9.54E-02 2.14E+01 5.59E+02 1.73E+03\n",
-      "37000 25 299.58 -1.50E-01 2.14E+01 5.56E+02 1.73E+03\n",
-      "37500 25 299.52 -1.58E-01 2.14E+01 5.62E+02 1.73E+03\n",
-      "38000 25 300.38 -2.50E-01 2.15E+01 5.51E+02 1.73E+03\n",
-      "38500 25 301.32 -2.23E-01 2.16E+01 5.66E+02 1.73E+03\n",
-      "39000 25 300.6 -1.49E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "39500 25 301.52 -4.11E-01 2.16E+01 5.48E+02 1.73E+03\n",
-      "40000 25 299.48 -1.75E-01 2.14E+01 5.67E+02 1.73E+03\n",
-      "40500 25 299.28 -1.53E-01 2.14E+01 5.59E+02 1.73E+03\n",
-      "41000 25 283.77 1.04E+00 2.03E+01 7.95E+02 1.73E+03\n",
-      "41500 25 299.08 -1.43E-01 2.14E+01 5.77E+02 1.73E+03\n",
-      "42000 25 300.35 -1.85E-01 2.15E+01 5.55E+02 1.73E+03\n",
-      "42500 25 300.66 -2.33E-01 2.15E+01 5.66E+02 1.73E+03\n",
-      "43000 25 302.61 -3.58E-01 2.16E+01 5.89E+02 1.73E+03\n",
-      "43500 25 298.36 -8.44E-02 2.13E+01 5.58E+02 1.73E+03\n",
-      "44000 25 299.61 -1.40E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "44500 25 299.82 -9.65E-02 2.14E+01 5.60E+02 1.73E+03\n",
-      "45000 25 300.88 -1.64E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "45500 25 301.72 -2.82E-01 2.16E+01 5.67E+02 1.73E+03\n",
-      "46000 25 295.66 8.59E-02 2.12E+01 6.25E+02 1.73E+03\n",
-      "46500 25 299.7 -9.17E-02 2.14E+01 5.60E+02 1.73E+03\n",
-      "47000 25 301.48 -2.88E-01 2.16E+01 5.66E+02 1.73E+03\n",
-      "47500 25 301.0 -2.18E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "48000 25 300.7 -2.05E-01 2.15E+01 5.62E+02 1.73E+03\n",
-      "48500 25 302.03 -2.85E-01 2.16E+01 5.71E+02 1.73E+03\n",
-      "49000 25 299.99 -1.33E-01 2.15E+01 6.13E+02 1.73E+03\n",
-      "49500 25 299.54 -7.61E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "50000 25 301.39 -2.53E-01 2.16E+01 5.57E+02 1.73E+03\n",
-      "50500 25 300.81 -2.74E-01 2.15E+01 5.87E+02 1.73E+03\n",
-      "51000 25 301.0 -2.55E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "51500 25 304.2 -5.06E-01 2.18E+01 5.46E+02 1.73E+03\n",
-      "52000 25 300.85 -2.57E-01 2.15E+01 5.82E+02 1.73E+03\n",
-      "52500 25 300.87 -2.55E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "53000 25 299.77 -1.49E-01 2.14E+01 5.56E+02 1.73E+03\n",
-      "53500 25 299.36 -9.22E-02 2.14E+01 5.60E+02 1.73E+03\n",
-      "54000 25 295.35 1.16E-01 2.11E+01 6.41E+02 1.73E+03\n",
-      "54500 25 291.52 4.29E-01 2.09E+01 6.91E+02 1.73E+03\n",
-      "55000 25 298.83 -1.39E-01 2.14E+01 5.55E+02 1.73E+03\n",
-      "55500 25 301.26 -2.92E-01 2.16E+01 5.64E+02 1.73E+03\n",
-      "56000 25 301.49 -2.91E-01 2.16E+01 5.65E+02 1.73E+03\n",
-      "56500 25 300.86 -1.67E-01 2.15E+01 5.66E+02 1.73E+03\n",
-      "57000 25 299.78 -1.20E-01 2.14E+01 5.90E+02 1.73E+03\n",
-      "57500 25 302.27 -3.59E-01 2.16E+01 5.93E+02 1.73E+03\n",
-      "58000 25 301.54 -3.01E-01 2.16E+01 5.61E+02 1.73E+03\n",
-      "58500 25 299.04 -1.54E-01 2.14E+01 5.54E+02 1.73E+03\n",
-      "59000 25 291.34 4.38E-01 2.08E+01 7.68E+02 1.73E+03\n",
-      "59500 25 301.8 -2.63E-01 2.16E+01 5.55E+02 1.73E+03\n",
-      "60000 25 301.34 -2.89E-01 2.16E+01 5.60E+02 1.73E+03\n",
-      "60500 25 299.67 -1.74E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "61000 25 299.51 -1.14E-01 2.14E+01 5.59E+02 1.73E+03\n",
-      "61500 25 300.04 -1.76E-01 2.15E+01 5.55E+02 1.73E+03\n",
-      "62000 25 299.42 -5.44E-02 2.14E+01 5.62E+02 1.73E+03\n",
-      "62500 25 299.92 -8.42E-02 2.15E+01 5.61E+02 1.73E+03\n",
-      "63000 25 301.05 -3.48E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "63500 25 300.55 -1.51E-01 2.15E+01 5.63E+02 1.73E+03\n",
-      "64000 25 280.86 1.25E+00 2.01E+01 8.72E+02 1.73E+03\n",
-      "64500 25 300.88 -2.43E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "65000 25 297.92 -1.71E-02 2.13E+01 6.65E+02 1.73E+03\n",
-      "65500 25 299.99 -1.62E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "66000 25 299.32 -6.96E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "66500 25 300.41 -1.15E-01 2.15E+01 5.60E+02 1.73E+03\n",
-      "67000 25 301.17 -2.02E-01 2.15E+01 5.96E+02 1.73E+03\n",
-      "67500 25 303.07 -3.58E-01 2.17E+01 5.55E+02 1.73E+03\n",
-      "68000 25 302.94 -4.10E-01 2.17E+01 5.49E+02 1.73E+03\n",
-      "68500 25 299.8 -1.76E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "69000 25 293.73 2.81E-01 2.10E+01 6.96E+02 1.73E+03\n",
-      "69500 25 300.08 -1.72E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "70000 25 298.6 -2.10E-01 2.14E+01 6.55E+02 1.73E+03\n",
-      "70500 25 299.59 -1.05E-01 2.14E+01 5.60E+02 1.73E+03\n",
-      "71000 25 301.13 -3.08E-01 2.15E+01 5.67E+02 1.73E+03\n",
-      "71500 25 299.16 -1.54E-01 2.14E+01 5.56E+02 1.73E+03\n",
-      "72000 25 299.94 -1.40E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "72500 25 298.72 -8.88E-02 2.14E+01 5.58E+02 1.73E+03\n",
-      "73000 25 300.66 -1.59E-01 2.15E+01 5.71E+02 1.73E+03\n",
-      "73500 25 302.05 -3.64E-01 2.16E+01 6.04E+02 1.73E+03\n",
-      "74000 25 300.4 -1.67E-01 2.15E+01 5.66E+02 1.73E+03\n",
-      "74500 25 298.52 -1.30E-01 2.14E+01 6.20E+02 1.73E+03\n",
-      "75000 25 302.8 -3.87E-01 2.17E+01 5.56E+02 1.73E+03\n",
-      "75500 25 299.88 -1.17E-01 2.15E+01 5.60E+02 1.73E+03\n",
-      "76000 25 297.35 9.18E-02 2.13E+01 6.30E+02 1.73E+03\n",
-      "76500 25 298.5 -9.31E-02 2.14E+01 5.93E+02 1.73E+03\n",
-      "77000 25 299.61 -8.55E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "77500 25 300.85 -1.75E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "78000 25 301.43 -2.98E-01 2.16E+01 5.50E+02 1.73E+03\n",
-      "78500 25 300.61 -2.14E-01 2.15E+01 5.53E+02 1.73E+03\n",
-      "79000 25 299.57 -1.39E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "79500 25 299.59 -1.03E-01 2.14E+01 5.59E+02 1.73E+03\n",
-      "80000 25 300.36 -1.90E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "80500 25 298.78 -6.00E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "81000 25 296.44 4.33E-02 2.12E+01 6.16E+02 1.73E+03\n",
-      "81500 25 301.78 -2.55E-01 2.16E+01 5.71E+02 1.73E+03\n",
-      "82000 25 299.22 -1.42E-01 2.14E+01 5.55E+02 1.73E+03\n",
-      "82500 25 299.34 -1.79E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "83000 25 300.63 -1.84E-01 2.15E+01 5.55E+02 1.73E+03\n",
-      "83500 25 304.01 -5.13E-01 2.17E+01 5.80E+02 1.73E+03\n",
-      "84000 25 300.49 -2.19E-01 2.15E+01 5.78E+02 1.73E+03\n",
-      "84500 25 300.5 -1.90E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "85000 25 299.5 -9.22E-02 2.14E+01 5.60E+02 1.73E+03\n",
-      "85500 25 301.15 -2.66E-01 2.15E+01 5.51E+02 1.73E+03\n",
-      "86000 25 301.59 -2.42E-01 2.16E+01 5.55E+02 1.73E+03\n",
-      "86500 25 299.38 -1.43E-01 2.14E+01 5.86E+02 1.73E+03\n",
-      "87000 25 302.25 -2.78E-01 2.16E+01 5.53E+02 1.73E+03\n",
-      "87500 25 302.36 -2.44E-01 2.16E+01 5.66E+02 1.73E+03\n",
-      "88000 25 301.26 -2.24E-01 2.16E+01 5.59E+02 1.73E+03\n",
-      "88500 25 300.69 -1.15E-01 2.15E+01 5.60E+02 1.73E+03\n",
-      "89000 25 302.56 -4.46E-01 2.16E+01 5.53E+02 1.73E+03\n",
-      "89500 25 302.25 -3.95E-01 2.16E+01 5.46E+02 1.73E+03\n",
-      "90000 25 299.41 -1.86E-01 2.14E+01 5.78E+02 1.73E+03\n",
-      "90500 25 300.56 -1.92E-01 2.15E+01 5.55E+02 1.73E+03\n",
-      "91000 25 302.58 -3.40E-01 2.16E+01 5.66E+02 1.73E+03\n",
-      "91500 25 301.78 -3.37E-01 2.16E+01 5.76E+02 1.73E+03\n",
-      "92000 25 300.59 -2.91E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "92500 25 299.83 -1.35E-01 2.14E+01 5.87E+02 1.73E+03\n",
-      "93000 25 301.08 -1.89E-01 2.15E+01 5.60E+02 1.73E+03\n",
-      "93500 25 301.27 -2.73E-01 2.16E+01 5.58E+02 1.73E+03\n",
-      "94000 25 299.04 -9.77E-02 2.14E+01 5.59E+02 1.73E+03\n",
-      "94500 25 299.72 -2.47E-01 2.14E+01 5.49E+02 1.73E+03\n",
-      "95000 25 301.32 -2.22E-01 2.16E+01 5.87E+02 1.73E+03\n",
-      "95500 25 300.28 -1.90E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "96000 25 299.2 -1.68E-01 2.14E+01 5.54E+02 1.73E+03\n",
-      "96500 25 299.97 -1.11E-01 2.15E+01 5.60E+02 1.73E+03\n",
-      "97000 25 299.09 -8.91E-02 2.14E+01 5.59E+02 1.73E+03\n",
-      "97500 25 296.06 1.00E-01 2.12E+01 6.33E+02 1.73E+03\n",
-      "98000 25 300.89 -1.91E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "98500 25 303.29 -4.01E-01 2.17E+01 5.94E+02 1.73E+03\n",
-      "99000 25 299.55 -1.57E-01 2.14E+01 5.56E+02 1.73E+03\n",
-      "99500 25 300.79 -2.24E-01 2.15E+01 5.53E+02 1.73E+03\n",
-      "100000 25 295.66 1.70E-01 2.12E+01 6.74E+02 1.73E+03\n",
-      "100500 25 305.11 -4.80E-01 2.18E+01 5.93E+02 1.73E+03\n",
-      "101000 25 300.87 -2.35E-01 2.15E+01 5.76E+02 1.73E+03\n",
-      "101500 25 300.27 -1.38E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "102000 25 296.84 1.17E-01 2.12E+01 6.40E+02 1.73E+03\n",
-      "102500 25 300.18 -2.13E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "103000 25 301.77 -3.35E-01 2.16E+01 5.84E+02 1.73E+03\n",
-      "103500 25 301.92 -4.21E-01 2.16E+01 5.57E+02 1.73E+03\n",
-      "104000 25 299.45 -1.16E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "104500 25 299.73 -1.72E-01 2.14E+01 5.59E+02 1.73E+03\n",
-      "105000 25 299.07 -1.22E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "105500 25 298.42 -5.01E-02 2.13E+01 5.61E+02 1.73E+03\n",
-      "106000 25 300.07 -2.01E-01 2.15E+01 5.67E+02 1.73E+03\n",
-      "106500 25 299.98 -1.18E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "107000 25 301.93 -4.06E-01 2.16E+01 5.61E+02 1.73E+03\n",
-      "107500 25 299.79 -1.50E-01 2.14E+01 5.56E+02 1.73E+03\n",
-      "108000 25 299.23 -7.22E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "108500 25 297.55 7.58E-02 2.13E+01 6.19E+02 1.73E+03\n",
-      "109000 25 300.95 -1.61E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "109500 25 300.82 -1.70E-01 2.15E+01 5.61E+02 1.73E+03\n",
-      "110000 25 299.24 -9.61E-02 2.14E+01 5.59E+02 1.73E+03\n",
-      "110500 25 299.63 -1.07E-01 2.14E+01 5.59E+02 1.73E+03\n",
-      "111000 25 300.13 -1.44E-01 2.15E+01 5.63E+02 1.73E+03\n",
-      "111500 25 299.3 -1.22E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "112000 25 301.31 -2.94E-01 2.16E+01 5.52E+02 1.73E+03\n",
-      "112500 25 299.4 -1.71E-01 2.14E+01 5.60E+02 1.73E+03\n",
-      "113000 25 299.7 -1.44E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "113500 25 302.49 -3.01E-01 2.16E+01 5.65E+02 1.73E+03\n",
-      "114000 25 301.95 -3.60E-01 2.16E+01 5.65E+02 1.73E+03\n",
-      "114500 25 300.19 -1.88E-01 2.15E+01 5.74E+02 1.73E+03\n",
-      "115000 25 299.72 -1.68E-01 2.14E+01 6.24E+02 1.73E+03\n",
-      "115500 25 301.02 -2.48E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "116000 25 297.79 -7.43E-02 2.13E+01 6.12E+02 1.73E+03\n",
-      "116500 25 301.29 -3.45E-01 2.16E+01 5.63E+02 1.73E+03\n",
-      "117000 25 299.54 -1.51E-01 2.14E+01 5.61E+02 1.73E+03\n",
-      "117500 25 298.65 -1.78E-01 2.14E+01 5.56E+02 1.73E+03\n",
-      "118000 25 293.5 1.86E-01 2.10E+01 6.98E+02 1.73E+03\n",
-      "118500 25 301.27 -2.71E-01 2.16E+01 5.61E+02 1.73E+03\n",
-      "119000 25 299.67 -1.35E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "119500 25 300.61 -2.07E-01 2.15E+01 5.61E+02 1.73E+03\n",
-      "120000 25 299.74 -1.90E-01 2.14E+01 5.67E+02 1.73E+03\n",
-      "120500 25 298.19 -7.06E-02 2.13E+01 5.59E+02 1.73E+03\n",
-      "121000 25 299.53 -4.36E-02 2.14E+01 5.63E+02 1.73E+03\n",
-      "121500 25 302.43 -3.10E-01 2.16E+01 5.66E+02 1.73E+03\n",
-      "122000 25 300.62 -1.78E-01 2.15E+01 5.61E+02 1.73E+03\n",
-      "122500 25 299.26 -1.82E-01 2.14E+01 5.53E+02 1.73E+03\n",
-      "123000 25 291.24 4.97E-01 2.08E+01 6.95E+02 1.73E+03\n",
-      "123500 25 301.78 -2.06E-01 2.16E+01 5.61E+02 1.73E+03\n",
-      "124000 25 300.56 -2.09E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "124500 25 302.46 -3.46E-01 2.16E+01 5.96E+02 1.73E+03\n",
-      "125000 25 300.0 -2.43E-01 2.15E+01 6.61E+02 1.73E+03\n",
-      "125500 25 297.88 5.42E-02 2.13E+01 6.48E+02 1.73E+03\n",
-      "126000 25 299.5 -1.60E-01 2.14E+01 5.55E+02 1.73E+03\n",
-      "126500 25 301.94 -2.98E-01 2.16E+01 5.53E+02 1.73E+03\n",
-      "127000 25 301.43 -2.53E-01 2.16E+01 5.67E+02 1.73E+03\n",
-      "127500 25 299.5 -7.85E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "128000 25 301.08 -2.26E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "128500 25 299.71 -2.02E-01 2.14E+01 5.53E+02 1.73E+03\n",
-      "129000 25 300.03 -1.50E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "129500 25 298.24 1.98E-02 2.13E+01 6.11E+02 1.73E+03\n",
-      "130000 25 302.59 -2.76E-01 2.16E+01 5.57E+02 1.73E+03\n",
-      "130500 25 298.91 -1.51E-01 2.14E+01 5.54E+02 1.73E+03\n",
-      "131000 25 297.56 -1.22E-01 2.13E+01 6.52E+02 1.73E+03\n",
-      "131500 25 299.16 -2.26E-01 2.14E+01 5.51E+02 1.73E+03\n",
-      "132000 25 301.19 -2.61E-01 2.15E+01 5.67E+02 1.73E+03\n",
-      "132500 25 299.05 -7.70E-02 2.14E+01 5.60E+02 1.73E+03\n",
-      "133000 25 300.44 -1.48E-01 2.15E+01 5.70E+02 1.73E+03\n",
-      "133500 25 299.44 -5.82E-02 2.14E+01 5.62E+02 1.73E+03\n",
-      "134000 25 303.51 -4.36E-01 2.17E+01 5.67E+02 1.73E+03\n",
-      "134500 25 294.96 6.97E-02 2.11E+01 6.26E+02 1.73E+03\n",
-      "135000 25 301.7 -2.57E-01 2.16E+01 5.54E+02 1.73E+03\n",
-      "135500 25 300.9 -3.09E-01 2.15E+01 5.48E+02 1.73E+03\n",
-      "136000 25 302.29 -3.44E-01 2.16E+01 5.52E+02 1.73E+03\n",
-      "136500 25 300.18 -1.38E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "137000 25 300.62 -2.00E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "137500 25 301.19 -2.39E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "138000 25 299.88 -2.09E-01 2.15E+01 5.53E+02 1.73E+03\n",
-      "138500 25 298.74 -4.15E-02 2.14E+01 5.62E+02 1.73E+03\n",
-      "139000 25 299.25 -6.58E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "139500 25 299.53 -1.39E-01 2.14E+01 5.63E+02 1.73E+03\n",
-      "140000 25 305.35 -5.99E-01 2.18E+01 5.68E+02 1.73E+03\n",
-      "140500 25 301.57 -2.82E-01 2.16E+01 5.58E+02 1.73E+03\n",
-      "141000 25 301.63 -3.06E-01 2.16E+01 5.64E+02 1.73E+03\n",
-      "141500 25 300.86 -3.47E-01 2.15E+01 5.52E+02 1.73E+03\n",
-      "142000 25 300.88 -2.12E-01 2.15E+01 5.55E+02 1.73E+03\n",
-      "142500 25 291.65 4.57E-01 2.09E+01 7.04E+02 1.73E+03\n",
-      "143000 25 302.88 -4.22E-01 2.17E+01 5.78E+02 1.73E+03\n",
-      "143500 25 299.66 -1.43E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "144000 25 299.55 -1.18E-01 2.14E+01 5.98E+02 1.73E+03\n",
-      "144500 25 299.85 -1.50E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "145000 25 300.75 -1.76E-01 2.15E+01 5.56E+02 1.73E+03\n",
-      "145500 25 298.63 -1.02E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "146000 25 284.53 9.29E-01 2.04E+01 7.70E+02 1.73E+03\n",
-      "146500 25 297.97 -1.33E-01 2.13E+01 5.54E+02 1.73E+03\n",
-      "147000 25 299.74 -6.56E-02 2.14E+01 5.62E+02 1.73E+03\n",
-      "147500 25 300.29 -1.75E-01 2.15E+01 5.63E+02 1.73E+03\n",
-      "148000 25 295.92 9.05E-02 2.12E+01 6.24E+02 1.73E+03\n",
-      "148500 25 299.68 -7.68E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "149000 25 300.5 -2.09E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "149500 25 300.66 -1.70E-01 2.15E+01 5.60E+02 1.73E+03\n",
-      "150000 25 301.76 -2.02E-01 2.16E+01 5.69E+02 1.73E+03\n",
-      "150500 25 301.08 -2.44E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "151000 25 300.09 -1.24E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "151500 25 299.43 -1.30E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "152000 25 296.75 8.68E-02 2.12E+01 6.66E+02 1.73E+03\n",
-      "152500 25 301.52 -2.55E-01 2.16E+01 5.60E+02 1.73E+03\n",
-      "153000 25 301.45 -2.32E-01 2.16E+01 5.61E+02 1.73E+03\n",
-      "153500 25 301.28 -2.27E-01 2.16E+01 5.74E+02 1.73E+03\n",
-      "154000 25 301.08 -1.64E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "154500 25 301.42 -2.74E-01 2.16E+01 5.63E+02 1.73E+03\n",
-      "155000 25 299.69 -8.65E-02 2.14E+01 5.60E+02 1.73E+03\n",
-      "155500 25 295.0 2.69E-01 2.11E+01 6.98E+02 1.73E+03\n",
-      "156000 25 300.97 -1.78E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "156500 25 299.38 -1.53E-01 2.14E+01 5.59E+02 1.73E+03\n",
-      "157000 25 301.49 -1.87E-01 2.16E+01 5.58E+02 1.73E+03\n",
-      "157500 25 299.27 -6.76E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "158000 25 299.11 -9.40E-02 2.14E+01 6.02E+02 1.73E+03\n",
-      "158500 25 295.29 2.28E-01 2.11E+01 6.55E+02 1.73E+03\n",
-      "159000 25 301.26 -1.87E-01 2.16E+01 5.61E+02 1.73E+03\n",
-      "159500 25 300.51 -1.54E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "160000 25 300.96 -1.88E-01 2.15E+01 5.72E+02 1.73E+03\n",
-      "160500 25 299.62 -1.41E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "161000 25 300.67 -2.01E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "161500 25 299.87 -2.08E-01 2.15E+01 5.81E+02 1.73E+03\n",
-      "162000 25 292.0 4.60E-01 2.09E+01 7.16E+02 1.73E+03\n",
-      "162500 25 302.94 -5.09E-01 2.17E+01 5.63E+02 1.73E+03\n",
-      "163000 25 295.29 2.49E-01 2.11E+01 6.51E+02 1.73E+03\n",
-      "163500 25 299.54 -2.45E-01 2.14E+01 5.50E+02 1.73E+03\n",
-      "164000 25 299.89 -1.39E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "164500 25 303.17 -3.73E-01 2.17E+01 5.52E+02 1.73E+03\n",
-      "165000 25 299.45 -9.69E-02 2.14E+01 5.59E+02 1.73E+03\n",
-      "165500 25 299.27 -1.21E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "166000 25 301.03 -1.56E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "166500 25 300.83 -2.47E-01 2.15E+01 5.62E+02 1.73E+03\n",
-      "167000 25 298.86 -1.07E-01 2.14E+01 7.26E+02 1.73E+03\n",
-      "167500 25 302.91 -3.54E-01 2.17E+01 5.56E+02 1.73E+03\n",
-      "168000 25 300.11 -2.23E-01 2.15E+01 5.87E+02 1.73E+03\n",
-      "168500 25 299.21 -1.08E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "169000 25 299.57 -8.36E-02 2.14E+01 5.86E+02 1.73E+03\n",
-      "169500 25 300.69 -2.43E-01 2.15E+01 5.55E+02 1.73E+03\n",
-      "170000 25 301.37 -2.37E-01 2.16E+01 5.54E+02 1.73E+03\n",
-      "170500 25 300.88 -1.58E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "171000 25 301.91 -3.15E-01 2.16E+01 5.51E+02 1.73E+03\n",
-      "171500 25 301.3 -3.26E-01 2.16E+01 5.54E+02 1.73E+03\n",
-      "172000 25 299.52 -1.33E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "172500 25 300.15 -1.60E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "173000 25 302.26 -2.44E-01 2.16E+01 5.60E+02 1.73E+03\n",
-      "173500 25 300.5 -3.57E-01 2.15E+01 5.55E+02 1.73E+03\n",
-      "174000 25 298.78 -1.77E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "174500 25 300.61 -3.09E-01 2.15E+01 5.49E+02 1.73E+03\n",
-      "175000 25 300.01 -1.48E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "175500 25 300.1 -2.97E-01 2.15E+01 5.52E+02 1.73E+03\n",
-      "176000 25 300.01 -1.93E-01 2.15E+01 5.55E+02 1.73E+03\n",
-      "176500 25 301.0 -1.69E-01 2.15E+01 6.06E+02 1.73E+03\n",
-      "177000 25 300.66 -1.58E-01 2.15E+01 5.61E+02 1.73E+03\n",
-      "177500 25 299.43 -1.79E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "178000 25 298.78 -9.62E-02 2.14E+01 5.58E+02 1.73E+03\n",
-      "178500 25 297.05 2.95E-02 2.13E+01 6.26E+02 1.73E+03\n",
-      "179000 25 299.19 -8.98E-02 2.14E+01 5.90E+02 1.73E+03\n",
-      "179500 25 300.99 -2.22E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "180000 25 298.91 -1.73E-01 2.14E+01 5.74E+02 1.73E+03\n",
-      "180500 25 298.66 -1.14E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "181000 25 298.74 -2.29E-01 2.14E+01 5.49E+02 1.73E+03\n",
-      "181500 25 300.76 -1.72E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "182000 25 300.8 -2.22E-01 2.15E+01 5.54E+02 1.73E+03\n",
-      "182500 25 295.69 1.31E-01 2.12E+01 6.47E+02 1.73E+03\n",
-      "183000 25 298.04 1.89E-03 2.13E+01 6.39E+02 1.73E+03\n",
-      "183500 25 301.46 -2.12E-01 2.16E+01 5.61E+02 1.73E+03\n",
-      "184000 25 300.54 -1.99E-01 2.15E+01 5.74E+02 1.73E+03\n",
-      "184500 25 300.53 -2.27E-01 2.15E+01 6.19E+02 1.73E+03\n",
-      "185000 25 300.13 -1.72E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "185500 25 301.69 -2.43E-01 2.16E+01 5.56E+02 1.73E+03\n",
-      "186000 25 300.17 -1.00E-01 2.15E+01 5.60E+02 1.73E+03\n",
-      "186500 25 300.47 -1.40E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "187000 25 299.83 -1.60E-01 2.14E+01 5.56E+02 1.73E+03\n",
-      "187500 25 298.8 -6.14E-02 2.14E+01 5.61E+02 1.73E+03\n",
-      "188000 25 298.31 -8.74E-02 2.13E+01 5.58E+02 1.73E+03\n",
-      "188500 25 302.09 -2.53E-01 2.16E+01 5.69E+02 1.73E+03\n",
-      "189000 25 300.37 -1.76E-01 2.15E+01 5.68E+02 1.73E+03\n",
-      "189500 25 299.27 -2.38E-01 2.14E+01 5.60E+02 1.73E+03\n",
-      "190000 25 300.47 -1.26E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "190500 25 301.92 -2.55E-01 2.16E+01 5.81E+02 1.73E+03\n",
-      "191000 25 301.07 -2.59E-01 2.15E+01 5.61E+02 1.73E+03\n",
-      "191500 25 301.28 -2.40E-01 2.16E+01 5.66E+02 1.73E+03\n",
-      "192000 25 299.35 -1.29E-01 2.14E+01 5.87E+02 1.73E+03\n",
-      "192500 25 299.38 -1.25E-01 2.14E+01 5.57E+02 1.73E+03\n",
-      "193000 25 299.66 -1.76E-01 2.14E+01 5.54E+02 1.73E+03\n",
-      "193500 25 301.22 -2.08E-01 2.15E+01 5.59E+02 1.73E+03\n",
-      "194000 25 301.71 -3.15E-01 2.16E+01 5.67E+02 1.73E+03\n",
-      "194500 25 300.39 -1.84E-01 2.15E+01 5.57E+02 1.73E+03\n",
-      "195000 25 300.63 -3.16E-01 2.15E+01 5.58E+02 1.73E+03\n",
-      "195500 25 298.91 -2.02E-01 2.14E+01 5.50E+02 1.73E+03\n",
-      "196000 25 300.05 -2.03E-01 2.15E+01 6.15E+02 1.73E+03\n",
-      "196500 25 300.18 -1.96E-01 2.15E+01 5.55E+02 1.73E+03\n",
-      "197000 25 299.81 -1.41E-01 2.14E+01 5.63E+02 1.73E+03\n",
-      "197500 25 298.87 -1.46E-01 2.14E+01 5.56E+02 1.73E+03\n",
-      "198000 25 299.47 -1.73E-01 2.14E+01 5.54E+02 1.73E+03\n",
-      "198500 25 301.37 -3.20E-01 2.16E+01 5.53E+02 1.73E+03\n",
-      "199000 25 299.0 -1.04E-01 2.14E+01 5.58E+02 1.73E+03\n",
-      "199500 25 299.79 -1.68E-01 2.14E+01 5.56E+02 1.73E+03\n",
-      "200000 25 299.46 -1.24E-01 2.14E+01 5.57E+02 1.73E+03\n"
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "sys.path.append(\"../../molecular-simulation/\")\n",
-    "from main import MolecularDynamics\n",
-    "\n",
-    "MolecularDynamics(number_atoms=25,\n",
-    "                    Lx=12,\n",
-    "                    maximum_steps=200000,\n",
-    "                    dimensions= 3,\n",
-    "                    desired_temperature=300,\n",
-    "                    tau_temp=100,\n",
-    "                    seed=21982,\n",
-    "                    thermo=500,\n",
-    "                    dump=500,\n",
-    "                    ).run()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/benchmark/python_25part_300K_NPT/run.ipynb b/benchmark/python_25part_300K_NPT/run.ipynb
deleted file mode 100644
index a081f62..0000000
--- a/benchmark/python_25part_300K_NPT/run.ipynb
+++ /dev/null
@@ -1,458 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "step N temp epot ekin press vol\n",
-      "0 25 92.27 -3.17E-01 6.60E+00 1.69E+02 1.73E+03\n",
-      "500 25 299.49 -2.38E-01 2.14E+01 3.12E+02 3.15E+03\n",
-      "1000 25 301.58 -2.03E-01 2.16E+01 2.41E+02 4.07E+03\n",
-      "1500 25 300.72 -1.09E-01 2.15E+01 2.16E+02 4.51E+03\n",
-      "2000 25 299.36 -1.90E-02 2.14E+01 2.05E+02 4.76E+03\n",
-      "2500 25 299.55 -4.49E-02 2.14E+01 2.03E+02 4.88E+03\n",
-      "3000 25 302.55 -1.08E-01 2.16E+01 2.03E+02 4.82E+03\n",
-      "3500 25 300.98 -1.84E-01 2.15E+01 2.09E+02 4.89E+03\n",
-      "4000 25 299.57 -2.27E-02 2.14E+01 2.01E+02 4.86E+03\n",
-      "4500 25 299.81 -3.11E-02 2.14E+01 1.98E+02 4.96E+03\n",
-      "5000 25 301.46 -1.44E-01 2.16E+01 2.11E+02 4.94E+03\n",
-      "5500 25 300.3 -1.15E-01 2.15E+01 2.12E+02 4.93E+03\n",
-      "6000 25 300.31 -2.55E-02 2.15E+01 2.01E+02 4.88E+03\n",
-      "6500 25 300.52 -6.86E-02 2.15E+01 1.97E+02 4.96E+03\n",
-      "7000 25 299.69 -5.47E-03 2.14E+01 1.98E+02 4.94E+03\n",
-      "7500 25 300.33 -1.24E-01 2.15E+01 1.97E+02 4.94E+03\n",
-      "8000 25 300.25 -4.07E-02 2.15E+01 1.98E+02 4.96E+03\n",
-      "8500 25 300.23 -7.96E-02 2.15E+01 2.04E+02 4.94E+03\n",
-      "9000 25 300.98 -1.29E-01 2.15E+01 1.59E+02 4.94E+03\n",
-      "9500 25 300.07 -4.35E-02 2.15E+01 2.01E+02 4.86E+03\n",
-      "10000 25 299.81 -4.48E-02 2.14E+01 2.00E+02 4.89E+03\n",
-      "10500 25 299.56 -1.36E-02 2.14E+01 2.00E+02 4.90E+03\n",
-      "11000 25 299.76 -1.95E-02 2.14E+01 1.99E+02 4.91E+03\n",
-      "11500 25 297.53 1.03E-01 2.13E+01 -2.04E+02 4.87E+03\n",
-      "12000 25 302.07 -1.61E-01 2.16E+01 1.99E+02 4.89E+03\n",
-      "12500 25 299.9 -2.26E-02 2.15E+01 2.00E+02 4.89E+03\n",
-      "13000 25 300.26 -1.37E-01 2.15E+01 2.08E+02 4.96E+03\n",
-      "13500 25 301.41 -2.56E-01 2.16E+01 2.02E+02 4.97E+03\n",
-      "14000 25 299.2 -1.52E-01 2.14E+01 1.95E+02 4.93E+03\n",
-      "14500 25 298.7 -4.16E-02 2.14E+01 1.97E+02 4.95E+03\n",
-      "15000 25 299.51 -3.56E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "15500 25 301.61 -1.99E-01 2.16E+01 1.98E+02 4.90E+03\n",
-      "16000 25 302.16 -1.22E-01 2.16E+01 1.90E+02 4.82E+03\n",
-      "16500 25 299.12 -2.96E-02 2.14E+01 2.00E+02 4.88E+03\n",
-      "17000 25 299.46 -1.20E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "17500 25 302.3 -2.56E-01 2.16E+01 1.99E+02 4.94E+03\n",
-      "18000 25 299.33 -1.19E-02 2.14E+01 1.99E+02 4.91E+03\n",
-      "18500 25 300.86 -1.15E-01 2.15E+01 1.98E+02 4.92E+03\n",
-      "19000 25 300.1 -3.26E-02 2.15E+01 1.99E+02 4.91E+03\n",
-      "19500 25 300.91 -1.24E-01 2.15E+01 1.98E+02 4.93E+03\n",
-      "20000 25 299.69 -1.11E-01 2.14E+01 2.03E+02 4.86E+03\n",
-      "20500 25 300.64 -1.99E-01 2.15E+01 1.98E+02 4.90E+03\n",
-      "21000 25 301.85 -1.97E-01 2.16E+01 1.99E+02 4.91E+03\n",
-      "21500 25 299.42 -5.14E-02 2.14E+01 1.98E+02 4.91E+03\n",
-      "22000 25 299.75 -3.98E-02 2.14E+01 1.97E+02 4.95E+03\n",
-      "22500 25 300.31 -1.38E-01 2.15E+01 2.00E+02 4.95E+03\n",
-      "23000 25 300.16 -3.96E-02 2.15E+01 1.98E+02 4.94E+03\n",
-      "23500 25 301.3 -1.47E-01 2.16E+01 1.96E+02 4.96E+03\n",
-      "24000 25 299.12 -1.22E-02 2.14E+01 1.98E+02 4.95E+03\n",
-      "24500 25 299.96 -2.30E-02 2.15E+01 2.02E+02 4.94E+03\n",
-      "25000 25 301.41 -1.40E-01 2.16E+01 2.11E+02 4.93E+03\n",
-      "25500 25 299.97 -8.96E-02 2.15E+01 2.05E+02 4.91E+03\n",
-      "26000 25 300.03 -6.85E-02 2.15E+01 2.02E+02 4.92E+03\n",
-      "26500 25 299.45 -9.49E-03 2.14E+01 1.99E+02 4.93E+03\n",
-      "27000 25 299.85 -8.65E-02 2.15E+01 1.95E+02 4.98E+03\n",
-      "27500 25 300.42 -1.07E-01 2.15E+01 1.99E+02 4.95E+03\n",
-      "28000 25 299.63 -3.30E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "28500 25 299.84 -4.91E-02 2.15E+01 2.00E+02 4.90E+03\n",
-      "29000 25 300.21 -4.35E-02 2.15E+01 1.99E+02 4.94E+03\n",
-      "29500 25 300.02 -6.85E-02 2.15E+01 2.06E+02 4.73E+03\n",
-      "30000 25 299.25 -2.77E-02 2.14E+01 2.02E+02 4.83E+03\n",
-      "30500 25 299.67 -1.00E-02 2.14E+01 2.02E+02 4.85E+03\n",
-      "31000 25 299.61 -1.94E-02 2.14E+01 2.00E+02 4.90E+03\n",
-      "31500 25 300.06 -4.40E-02 2.15E+01 1.99E+02 4.92E+03\n",
-      "32000 25 299.45 -2.01E-02 2.14E+01 1.97E+02 4.95E+03\n",
-      "32500 25 301.32 -1.27E-01 2.16E+01 1.95E+02 4.98E+03\n",
-      "33000 25 300.62 -1.12E-01 2.15E+01 1.96E+02 4.96E+03\n",
-      "33500 25 301.21 -1.58E-01 2.15E+01 1.97E+02 4.93E+03\n",
-      "34000 25 300.48 -1.47E-01 2.15E+01 1.96E+02 4.93E+03\n",
-      "34500 25 301.09 -1.18E-01 2.15E+01 1.97E+02 4.94E+03\n",
-      "35000 25 300.42 -7.27E-02 2.15E+01 2.08E+02 4.96E+03\n",
-      "35500 25 296.62 1.97E-01 2.12E+01 -3.09E+02 4.87E+03\n",
-      "36000 25 296.54 1.53E-01 2.12E+01 2.30E+02 4.82E+03\n",
-      "36500 25 299.96 -9.56E-02 2.15E+01 2.02E+02 4.88E+03\n",
-      "37000 25 301.77 -1.73E-01 2.16E+01 1.99E+02 4.91E+03\n",
-      "37500 25 300.82 -1.44E-01 2.15E+01 1.96E+02 4.93E+03\n",
-      "38000 25 298.06 3.76E-02 2.13E+01 2.22E+02 4.95E+03\n",
-      "38500 25 300.59 -1.12E-01 2.15E+01 2.04E+02 4.95E+03\n",
-      "39000 25 299.68 -5.22E-02 2.14E+01 2.12E+02 4.80E+03\n",
-      "39500 25 299.79 -5.57E-02 2.14E+01 2.00E+02 4.87E+03\n",
-      "40000 25 299.89 -3.48E-02 2.15E+01 2.00E+02 4.90E+03\n",
-      "40500 25 300.09 -3.30E-02 2.15E+01 1.99E+02 4.92E+03\n",
-      "41000 25 300.89 -1.53E-01 2.15E+01 1.97E+02 4.91E+03\n",
-      "41500 25 300.89 -1.11E-01 2.15E+01 1.97E+02 4.94E+03\n",
-      "42000 25 300.47 -1.15E-01 2.15E+01 2.06E+02 4.92E+03\n",
-      "42500 25 299.66 -4.21E-02 2.14E+01 1.99E+02 4.91E+03\n",
-      "43000 25 299.78 -1.14E-02 2.14E+01 1.99E+02 4.94E+03\n",
-      "43500 25 299.78 -3.07E-02 2.14E+01 2.07E+02 4.77E+03\n",
-      "44000 25 301.05 -1.11E-01 2.15E+01 2.03E+02 4.84E+03\n",
-      "44500 25 299.67 -3.24E-02 2.14E+01 2.00E+02 4.89E+03\n",
-      "45000 25 300.6 -8.96E-02 2.15E+01 2.00E+02 4.90E+03\n",
-      "45500 25 301.11 -1.37E-01 2.15E+01 1.98E+02 4.91E+03\n",
-      "46000 25 299.98 -7.56E-02 2.15E+01 1.97E+02 4.92E+03\n",
-      "46500 25 300.62 -1.19E-01 2.15E+01 1.99E+02 4.92E+03\n",
-      "47000 25 299.35 -1.91E-02 2.14E+01 2.01E+02 4.87E+03\n",
-      "47500 25 300.75 -1.49E-01 2.15E+01 2.02E+02 4.88E+03\n",
-      "48000 25 300.56 -1.29E-01 2.15E+01 2.00E+02 4.90E+03\n",
-      "48500 25 298.51 5.96E-02 2.14E+01 2.25E+02 4.94E+03\n",
-      "49000 25 299.41 -3.31E-02 2.14E+01 2.02E+02 4.83E+03\n",
-      "49500 25 299.97 -1.32E-02 2.15E+01 2.02E+02 4.86E+03\n",
-      "50000 25 300.95 -1.34E-01 2.15E+01 2.00E+02 4.91E+03\n",
-      "50500 25 299.26 -6.57E-02 2.14E+01 1.99E+02 4.93E+03\n",
-      "51000 25 300.22 -8.70E-02 2.15E+01 2.01E+02 4.94E+03\n",
-      "51500 25 299.7 -8.67E-03 2.14E+01 1.98E+02 4.94E+03\n",
-      "52000 25 301.78 -1.29E-01 2.16E+01 2.01E+02 4.84E+03\n",
-      "52500 25 300.48 -7.36E-02 2.15E+01 2.00E+02 4.88E+03\n",
-      "53000 25 300.06 -3.34E-02 2.15E+01 2.00E+02 4.90E+03\n",
-      "53500 25 300.58 -7.00E-02 2.15E+01 2.03E+02 4.91E+03\n",
-      "54000 25 299.69 -2.98E-02 2.14E+01 1.98E+02 4.93E+03\n",
-      "54500 25 299.93 -6.00E-02 2.15E+01 1.96E+02 4.97E+03\n",
-      "55000 25 300.14 -6.12E-02 2.15E+01 1.99E+02 4.96E+03\n",
-      "55500 25 300.96 -1.78E-01 2.15E+01 2.08E+02 4.92E+03\n",
-      "56000 25 300.29 -3.86E-02 2.15E+01 1.98E+02 4.95E+03\n",
-      "56500 25 301.15 -1.00E-01 2.15E+01 1.97E+02 4.95E+03\n",
-      "57000 25 299.7 -3.71E-02 2.14E+01 1.99E+02 4.94E+03\n",
-      "57500 25 300.42 -1.10E-01 2.15E+01 2.05E+02 4.92E+03\n",
-      "58000 25 300.74 -9.23E-02 2.15E+01 1.98E+02 4.92E+03\n",
-      "58500 25 298.61 2.73E-02 2.14E+01 2.14E+02 4.91E+03\n",
-      "59000 25 299.69 -1.20E-02 2.14E+01 1.99E+02 4.95E+03\n",
-      "59500 25 299.38 -2.88E-02 2.14E+01 1.98E+02 4.95E+03\n",
-      "60000 25 298.9 -6.03E-02 2.14E+01 2.06E+02 4.98E+03\n",
-      "60500 25 300.51 -1.64E-01 2.15E+01 1.95E+02 4.98E+03\n",
-      "61000 25 299.34 -5.67E-03 2.14E+01 1.97E+02 4.96E+03\n",
-      "61500 25 301.58 -1.43E-01 2.16E+01 2.07E+02 4.98E+03\n",
-      "62000 25 299.79 -1.71E-02 2.14E+01 2.01E+02 4.90E+03\n",
-      "62500 25 293.17 4.21E-01 2.10E+01 2.36E+02 4.97E+03\n",
-      "63000 25 300.53 -1.07E-01 2.15E+01 1.96E+02 4.95E+03\n",
-      "63500 25 300.11 -4.80E-02 2.15E+01 1.98E+02 4.94E+03\n",
-      "64000 25 299.99 -3.10E-02 2.15E+01 1.98E+02 4.93E+03\n",
-      "64500 25 299.59 -5.45E-02 2.14E+01 1.97E+02 4.95E+03\n",
-      "65000 25 300.17 -3.31E-02 2.15E+01 1.98E+02 4.92E+03\n",
-      "65500 25 299.1 -2.02E-02 2.14E+01 1.98E+02 4.92E+03\n",
-      "66000 25 300.23 -7.24E-02 2.15E+01 1.97E+02 4.96E+03\n",
-      "66500 25 299.74 -1.47E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "67000 25 299.41 -9.11E-03 2.14E+01 1.97E+02 4.97E+03\n",
-      "67500 25 300.78 -1.69E-01 2.15E+01 1.95E+02 4.96E+03\n",
-      "68000 25 301.04 -1.64E-01 2.15E+01 2.05E+02 4.73E+03\n",
-      "68500 25 300.96 -1.28E-01 2.15E+01 2.05E+02 4.80E+03\n",
-      "69000 25 301.03 -1.53E-01 2.15E+01 2.00E+02 4.87E+03\n",
-      "69500 25 299.6 -7.28E-02 2.14E+01 2.12E+02 4.92E+03\n",
-      "70000 25 300.35 -1.30E-01 2.15E+01 2.05E+02 4.87E+03\n",
-      "70500 25 299.48 -2.77E-02 2.14E+01 2.01E+02 4.91E+03\n",
-      "71000 25 299.16 -1.84E-02 2.14E+01 1.99E+02 4.94E+03\n",
-      "71500 25 299.74 -1.12E-02 2.14E+01 1.99E+02 4.94E+03\n",
-      "72000 25 299.74 -9.90E-02 2.14E+01 2.07E+02 4.93E+03\n",
-      "72500 25 299.49 -6.43E-02 2.14E+01 2.00E+02 4.88E+03\n",
-      "73000 25 301.27 -1.80E-01 2.16E+01 2.00E+02 4.93E+03\n",
-      "73500 25 300.31 -7.84E-02 2.15E+01 2.05E+02 4.93E+03\n",
-      "74000 25 300.89 -1.19E-01 2.15E+01 1.96E+02 4.95E+03\n",
-      "74500 25 300.17 -4.73E-02 2.15E+01 1.98E+02 4.92E+03\n",
-      "75000 25 299.6 -6.09E-03 2.14E+01 2.01E+02 4.86E+03\n",
-      "75500 25 300.67 -1.20E-01 2.15E+01 2.00E+02 4.90E+03\n",
-      "76000 25 301.1 -1.02E-01 2.15E+01 2.01E+02 4.89E+03\n",
-      "76500 25 299.53 -5.42E-02 2.14E+01 1.99E+02 4.89E+03\n",
-      "77000 25 299.71 -2.19E-02 2.14E+01 2.05E+02 4.81E+03\n",
-      "77500 25 299.95 -1.47E-01 2.15E+01 2.01E+02 4.83E+03\n",
-      "78000 25 301.5 -2.18E-01 2.16E+01 2.01E+02 4.87E+03\n",
-      "78500 25 299.92 -1.29E-02 2.15E+01 2.01E+02 4.87E+03\n",
-      "79000 25 300.03 -7.32E-02 2.15E+01 1.99E+02 4.88E+03\n",
-      "79500 25 300.09 -3.61E-02 2.15E+01 1.98E+02 4.94E+03\n",
-      "80000 25 300.41 -1.11E-01 2.15E+01 1.96E+02 4.96E+03\n",
-      "80500 25 300.28 -5.57E-02 2.15E+01 1.99E+02 4.94E+03\n",
-      "81000 25 300.67 -1.31E-01 2.15E+01 1.96E+02 4.97E+03\n",
-      "81500 25 300.32 -4.39E-02 2.15E+01 1.97E+02 4.95E+03\n",
-      "82000 25 299.81 -7.90E-03 2.14E+01 1.98E+02 4.95E+03\n",
-      "82500 25 299.79 -1.52E-02 2.14E+01 2.03E+02 4.84E+03\n",
-      "83000 25 299.28 -5.15E-02 2.14E+01 2.00E+02 4.87E+03\n",
-      "83500 25 299.52 -2.89E-02 2.14E+01 2.00E+02 4.89E+03\n",
-      "84000 25 300.91 -1.29E-01 2.15E+01 1.97E+02 4.93E+03\n",
-      "84500 25 300.09 -1.18E-01 2.15E+01 2.02E+02 4.96E+03\n",
-      "85000 25 302.0 -2.44E-01 2.16E+01 2.00E+02 4.96E+03\n",
-      "85500 25 300.87 -1.07E-01 2.15E+01 2.00E+02 4.95E+03\n",
-      "86000 25 300.01 -3.16E-02 2.15E+01 2.02E+02 4.85E+03\n",
-      "86500 25 300.51 -1.04E-01 2.15E+01 2.00E+02 4.88E+03\n",
-      "87000 25 299.71 -2.61E-02 2.14E+01 2.00E+02 4.88E+03\n",
-      "87500 25 299.88 -5.37E-02 2.15E+01 2.00E+02 4.89E+03\n",
-      "88000 25 300.2 -7.26E-02 2.15E+01 1.98E+02 4.90E+03\n",
-      "88500 25 300.79 -9.76E-02 2.15E+01 1.98E+02 4.92E+03\n",
-      "89000 25 301.74 -1.70E-01 2.16E+01 2.14E+02 4.69E+03\n",
-      "89500 25 301.95 -2.15E-01 2.16E+01 2.11E+02 4.81E+03\n",
-      "90000 25 299.99 -8.70E-02 2.15E+01 2.00E+02 4.87E+03\n",
-      "90500 25 299.67 -2.06E-02 2.14E+01 1.99E+02 4.95E+03\n",
-      "91000 25 299.78 -2.57E-02 2.14E+01 1.98E+02 4.96E+03\n",
-      "91500 25 300.09 -5.79E-02 2.15E+01 2.05E+02 4.95E+03\n",
-      "92000 25 301.33 -1.76E-01 2.16E+01 1.96E+02 4.95E+03\n",
-      "92500 25 300.1 -5.61E-02 2.15E+01 1.98E+02 4.93E+03\n",
-      "93000 25 299.4 -4.35E-02 2.14E+01 1.99E+02 4.91E+03\n",
-      "93500 25 299.8 -2.13E-02 2.14E+01 1.99E+02 4.93E+03\n",
-      "94000 25 300.68 -1.12E-01 2.15E+01 1.98E+02 4.92E+03\n",
-      "94500 25 300.5 -9.90E-02 2.15E+01 2.00E+02 4.88E+03\n",
-      "95000 25 299.47 -2.95E-02 2.14E+01 1.99E+02 4.90E+03\n",
-      "95500 25 297.5 1.20E-01 2.13E+01 2.25E+02 4.80E+03\n",
-      "96000 25 300.13 -4.23E-02 2.15E+01 1.99E+02 4.90E+03\n",
-      "96500 25 299.78 -1.78E-02 2.14E+01 1.99E+02 4.92E+03\n",
-      "97000 25 299.77 -5.69E-03 2.14E+01 2.00E+02 4.92E+03\n",
-      "97500 25 299.57 -1.10E-02 2.14E+01 2.00E+02 4.90E+03\n",
-      "98000 25 299.64 -5.85E-02 2.14E+01 1.97E+02 4.94E+03\n",
-      "98500 25 299.12 -1.67E-02 2.14E+01 1.99E+02 4.92E+03\n",
-      "99000 25 299.97 -2.38E-02 2.15E+01 1.98E+02 4.94E+03\n",
-      "99500 25 300.25 -4.51E-02 2.15E+01 1.97E+02 4.95E+03\n",
-      "100000 25 300.37 -5.92E-02 2.15E+01 1.97E+02 4.95E+03\n",
-      "100500 25 299.95 -8.40E-02 2.15E+01 1.97E+02 4.93E+03\n",
-      "101000 25 300.66 -1.38E-01 2.15E+01 1.97E+02 4.92E+03\n",
-      "101500 25 299.97 -1.07E-01 2.15E+01 2.02E+02 4.95E+03\n",
-      "102000 25 299.53 -1.64E-02 2.14E+01 1.98E+02 4.93E+03\n",
-      "102500 25 299.63 -7.33E-02 2.14E+01 2.09E+02 4.94E+03\n",
-      "103000 25 299.95 -1.39E-02 2.15E+01 1.98E+02 4.94E+03\n",
-      "103500 25 299.72 -1.82E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "104000 25 300.92 -9.44E-02 2.15E+01 1.98E+02 4.93E+03\n",
-      "104500 25 298.29 1.22E-01 2.13E+01 2.19E+02 4.95E+03\n",
-      "105000 25 300.59 -7.94E-02 2.15E+01 2.07E+02 4.94E+03\n",
-      "105500 25 300.28 -3.62E-02 2.15E+01 2.02E+02 4.96E+03\n",
-      "106000 25 299.87 -1.15E-02 2.15E+01 1.98E+02 4.95E+03\n",
-      "106500 25 299.69 -2.56E-02 2.14E+01 2.01E+02 4.86E+03\n",
-      "107000 25 299.53 -2.87E-02 2.14E+01 1.99E+02 4.92E+03\n",
-      "107500 25 301.31 -1.27E-01 2.16E+01 1.97E+02 4.94E+03\n",
-      "108000 25 300.74 -1.07E-01 2.15E+01 2.03E+02 4.85E+03\n",
-      "108500 25 299.48 -9.12E-03 2.14E+01 2.01E+02 4.87E+03\n",
-      "109000 25 299.79 -1.06E-01 2.14E+01 2.01E+02 4.89E+03\n",
-      "109500 25 300.34 -9.70E-02 2.15E+01 1.98E+02 4.91E+03\n",
-      "110000 25 299.93 -7.57E-02 2.15E+01 1.99E+02 4.94E+03\n",
-      "110500 25 300.37 -6.87E-02 2.15E+01 2.04E+02 4.81E+03\n",
-      "111000 25 299.92 -2.68E-02 2.15E+01 2.01E+02 4.87E+03\n",
-      "111500 25 301.39 -1.38E-01 2.16E+01 1.75E+02 4.80E+03\n",
-      "112000 25 301.03 -1.64E-01 2.15E+01 2.16E+02 4.68E+03\n",
-      "112500 25 280.75 1.34E+00 2.01E+01 2.97E+02 4.82E+03\n",
-      "113000 25 300.03 -5.89E-02 2.15E+01 2.02E+02 4.84E+03\n",
-      "113500 25 301.16 -1.14E-01 2.15E+01 2.00E+02 4.89E+03\n",
-      "114000 25 302.17 -1.93E-01 2.16E+01 1.98E+02 4.95E+03\n",
-      "114500 25 299.37 -1.86E-02 2.14E+01 1.98E+02 4.93E+03\n",
-      "115000 25 299.51 -8.93E-02 2.14E+01 2.06E+02 4.98E+03\n",
-      "115500 25 301.1 -1.89E-01 2.15E+01 2.21E+02 4.98E+03\n",
-      "116000 25 298.89 -7.17E-02 2.14E+01 1.94E+02 4.99E+03\n",
-      "116500 25 300.05 -9.32E-03 2.15E+01 1.97E+02 4.98E+03\n",
-      "117000 25 299.24 -3.30E-02 2.14E+01 1.97E+02 4.96E+03\n",
-      "117500 25 301.47 -5.72E-02 2.16E+01 2.16E+02 4.76E+03\n",
-      "118000 25 299.65 -4.65E-02 2.14E+01 2.09E+02 4.86E+03\n",
-      "118500 25 299.61 -1.74E-02 2.14E+01 2.00E+02 4.89E+03\n",
-      "119000 25 298.61 -2.01E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "119500 25 299.08 -2.60E-02 2.14E+01 2.13E+02 4.92E+03\n",
-      "120000 25 299.72 -4.77E-02 2.14E+01 2.03E+02 4.80E+03\n",
-      "120500 25 299.76 -4.60E-02 2.14E+01 2.00E+02 4.88E+03\n",
-      "121000 25 299.22 -1.52E-02 2.14E+01 1.98E+02 4.92E+03\n",
-      "121500 25 300.11 -9.92E-02 2.15E+01 1.97E+02 4.94E+03\n",
-      "122000 25 300.33 -7.67E-02 2.15E+01 1.98E+02 4.93E+03\n",
-      "122500 25 299.02 -4.40E-03 2.14E+01 2.00E+02 4.89E+03\n",
-      "123000 25 299.79 -6.12E-02 2.14E+01 1.99E+02 4.90E+03\n",
-      "123500 25 300.0 -4.24E-02 2.15E+01 1.98E+02 4.92E+03\n",
-      "124000 25 300.7 -1.18E-01 2.15E+01 1.99E+02 4.92E+03\n",
-      "124500 25 300.48 -7.65E-02 2.15E+01 1.99E+02 4.91E+03\n",
-      "125000 25 300.85 -1.26E-01 2.15E+01 2.04E+02 4.90E+03\n",
-      "125500 25 301.92 -2.57E-01 2.16E+01 2.02E+02 4.91E+03\n",
-      "126000 25 299.87 -8.78E-03 2.15E+01 1.99E+02 4.94E+03\n",
-      "126500 25 299.82 -3.63E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "127000 25 300.05 -2.75E-02 2.15E+01 1.98E+02 4.93E+03\n",
-      "127500 25 299.58 -2.10E-02 2.14E+01 1.99E+02 4.92E+03\n",
-      "128000 25 301.62 -2.13E-01 2.16E+01 2.00E+02 4.94E+03\n",
-      "128500 25 299.64 -3.76E-02 2.14E+01 1.98E+02 4.93E+03\n",
-      "129000 25 300.4 -1.09E-01 2.15E+01 2.06E+02 4.95E+03\n",
-      "129500 25 299.61 -9.69E-02 2.14E+01 2.00E+02 4.93E+03\n",
-      "130000 25 299.78 -1.01E-02 2.14E+01 1.99E+02 4.94E+03\n",
-      "130500 25 300.49 -8.62E-02 2.15E+01 2.11E+02 4.93E+03\n",
-      "131000 25 300.18 -1.14E-01 2.15E+01 1.97E+02 4.92E+03\n",
-      "131500 25 299.56 -3.86E-02 2.14E+01 1.97E+02 4.94E+03\n",
-      "132000 25 299.47 -1.05E-02 2.14E+01 1.99E+02 4.93E+03\n",
-      "132500 25 301.26 -1.63E-01 2.16E+01 2.05E+02 4.90E+03\n",
-      "133000 25 299.64 -3.87E-02 2.14E+01 1.99E+02 4.93E+03\n",
-      "133500 25 299.58 -1.43E-02 2.14E+01 1.99E+02 4.92E+03\n",
-      "134000 25 300.23 -1.01E-01 2.15E+01 1.98E+02 4.92E+03\n",
-      "134500 25 300.72 -1.29E-01 2.15E+01 1.98E+02 4.94E+03\n",
-      "135000 25 299.06 -1.14E-02 2.14E+01 2.01E+02 4.86E+03\n",
-      "135500 25 299.89 -7.59E-02 2.15E+01 2.09E+02 4.93E+03\n",
-      "136000 25 290.52 5.68E-01 2.08E+01 2.51E+02 4.98E+03\n",
-      "136500 25 301.61 -1.95E-01 2.16E+01 2.05E+02 4.98E+03\n",
-      "137000 25 299.6 -1.28E-02 2.14E+01 1.98E+02 4.95E+03\n",
-      "137500 25 300.28 -7.72E-02 2.15E+01 1.97E+02 4.93E+03\n",
-      "138000 25 299.12 -7.85E-02 2.14E+01 2.01E+02 4.85E+03\n",
-      "138500 25 301.64 -2.63E-01 2.16E+01 2.01E+02 4.89E+03\n",
-      "139000 25 300.61 -1.49E-01 2.15E+01 1.98E+02 4.91E+03\n",
-      "139500 25 299.76 -2.33E-02 2.14E+01 2.02E+02 4.85E+03\n",
-      "140000 25 299.49 -2.27E-02 2.14E+01 2.02E+02 4.92E+03\n",
-      "140500 25 302.18 -4.05E-01 2.16E+01 2.09E+02 4.87E+03\n",
-      "141000 25 300.5 -7.73E-02 2.15E+01 1.99E+02 4.89E+03\n",
-      "141500 25 299.42 -3.23E-02 2.14E+01 2.13E+02 4.89E+03\n",
-      "142000 25 299.92 -6.82E-02 2.15E+01 2.02E+02 4.90E+03\n",
-      "142500 25 300.3 -3.82E-02 2.15E+01 1.98E+02 4.93E+03\n",
-      "143000 25 300.4 -4.91E-02 2.15E+01 2.07E+02 4.94E+03\n",
-      "143500 25 300.94 -1.70E-01 2.15E+01 1.96E+02 4.94E+03\n",
-      "144000 25 299.61 -1.56E-02 2.14E+01 1.99E+02 4.93E+03\n",
-      "144500 25 299.81 -9.47E-02 2.14E+01 1.98E+02 4.92E+03\n",
-      "145000 25 299.9 -3.09E-02 2.15E+01 1.98E+02 4.92E+03\n",
-      "145500 25 303.24 -3.31E-01 2.17E+01 1.99E+02 5.00E+03\n",
-      "146000 25 299.78 -2.60E-02 2.14E+01 1.97E+02 4.96E+03\n",
-      "146500 25 301.63 -9.92E-02 2.16E+01 2.09E+02 4.67E+03\n",
-      "147000 25 300.37 -5.04E-02 2.15E+01 2.09E+02 4.72E+03\n",
-      "147500 25 300.02 -6.01E-02 2.15E+01 2.06E+02 4.84E+03\n",
-      "148000 25 299.88 -7.66E-02 2.15E+01 2.13E+02 4.90E+03\n",
-      "148500 25 301.09 -1.75E-01 2.15E+01 2.10E+02 4.68E+03\n",
-      "149000 25 300.25 -1.46E-01 2.15E+01 2.14E+02 4.84E+03\n",
-      "149500 25 299.87 -8.19E-02 2.15E+01 2.02E+02 4.92E+03\n",
-      "150000 25 301.45 -1.90E-01 2.16E+01 2.00E+02 4.89E+03\n",
-      "150500 25 300.12 -5.18E-02 2.15E+01 1.99E+02 4.89E+03\n",
-      "151000 25 300.17 -8.66E-03 2.15E+01 1.99E+02 4.93E+03\n",
-      "151500 25 299.54 -5.43E-02 2.14E+01 1.97E+02 4.96E+03\n",
-      "152000 25 300.89 -1.16E-01 2.15E+01 2.00E+02 4.85E+03\n",
-      "152500 25 299.53 -4.78E-02 2.14E+01 1.99E+02 4.89E+03\n",
-      "153000 25 300.18 -6.13E-02 2.15E+01 1.99E+02 4.90E+03\n",
-      "153500 25 292.32 5.09E-01 2.09E+01 2.46E+02 4.90E+03\n",
-      "154000 25 299.98 -4.94E-02 2.15E+01 1.98E+02 4.92E+03\n",
-      "154500 25 288.52 6.95E-01 2.06E+01 2.70E+02 4.96E+03\n",
-      "155000 25 300.13 -8.80E-02 2.15E+01 1.97E+02 4.93E+03\n",
-      "155500 25 300.33 -1.16E-01 2.15E+01 2.13E+02 4.88E+03\n",
-      "156000 25 300.84 -1.07E-01 2.15E+01 1.99E+02 4.92E+03\n",
-      "156500 25 300.7 -1.65E-01 2.15E+01 1.98E+02 4.94E+03\n",
-      "157000 25 299.61 -2.11E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "157500 25 299.83 -2.48E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "158000 25 299.3 -2.69E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "158500 25 302.49 -2.21E-01 2.16E+01 2.05E+02 4.92E+03\n",
-      "159000 25 299.36 -2.38E-02 2.14E+01 1.98E+02 4.93E+03\n",
-      "159500 25 299.79 -2.10E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "160000 25 299.62 -9.24E-03 2.14E+01 1.98E+02 4.94E+03\n",
-      "160500 25 299.85 -1.83E-02 2.15E+01 1.97E+02 4.96E+03\n",
-      "161000 25 300.49 -7.69E-02 2.15E+01 2.14E+02 4.96E+03\n",
-      "161500 25 300.62 -9.31E-02 2.15E+01 1.97E+02 4.94E+03\n",
-      "162000 25 300.01 -3.29E-02 2.15E+01 1.98E+02 4.92E+03\n",
-      "162500 25 300.0 -1.56E-01 2.15E+01 2.26E+02 4.94E+03\n",
-      "163000 25 299.85 -7.59E-02 2.15E+01 2.05E+02 4.94E+03\n",
-      "163500 25 300.71 -1.09E-01 2.15E+01 2.00E+02 4.91E+03\n",
-      "164000 25 299.95 -3.88E-02 2.15E+01 1.99E+02 4.91E+03\n",
-      "164500 25 299.87 -7.49E-02 2.15E+01 1.97E+02 4.96E+03\n",
-      "165000 25 302.03 -2.96E-01 2.16E+01 1.95E+02 4.97E+03\n",
-      "165500 25 300.97 -1.23E-01 2.15E+01 2.01E+02 4.95E+03\n",
-      "166000 25 300.83 -1.46E-01 2.15E+01 1.97E+02 4.93E+03\n",
-      "166500 25 300.2 -1.16E-01 2.15E+01 1.97E+02 4.93E+03\n",
-      "167000 25 299.15 -4.69E-02 2.14E+01 1.97E+02 4.94E+03\n",
-      "167500 25 300.06 -6.28E-02 2.15E+01 2.09E+02 4.85E+03\n",
-      "168000 25 300.63 -8.54E-02 2.15E+01 2.22E+02 4.80E+03\n",
-      "168500 25 300.52 -1.22E-01 2.15E+01 1.99E+02 4.87E+03\n",
-      "169000 25 293.39 3.41E-01 2.10E+01 2.38E+02 4.91E+03\n",
-      "169500 25 300.62 -7.83E-02 2.15E+01 1.98E+02 4.92E+03\n",
-      "170000 25 299.83 -6.29E-02 2.14E+01 1.98E+02 4.93E+03\n",
-      "170500 25 299.51 -2.53E-02 2.14E+01 2.00E+02 4.95E+03\n",
-      "171000 25 300.22 -1.13E-01 2.15E+01 2.00E+02 4.98E+03\n",
-      "171500 25 300.36 -6.48E-03 2.15E+01 2.04E+02 4.82E+03\n",
-      "172000 25 299.56 -9.30E-03 2.14E+01 2.00E+02 4.89E+03\n",
-      "172500 25 299.57 -2.03E-02 2.14E+01 1.99E+02 4.91E+03\n",
-      "173000 25 301.73 -1.94E-01 2.16E+01 1.98E+02 4.93E+03\n",
-      "173500 25 300.24 -6.29E-02 2.15E+01 1.96E+02 4.97E+03\n",
-      "174000 25 299.75 -8.51E-03 2.14E+01 2.00E+02 4.89E+03\n",
-      "174500 25 299.35 -6.88E-03 2.14E+01 2.01E+02 4.87E+03\n",
-      "175000 25 300.93 -9.24E-02 2.15E+01 2.10E+02 4.91E+03\n",
-      "175500 25 300.78 -1.01E-01 2.15E+01 1.99E+02 4.91E+03\n",
-      "176000 25 300.93 -1.20E-01 2.15E+01 2.00E+02 4.92E+03\n",
-      "176500 25 300.25 -1.55E-01 2.15E+01 1.99E+02 4.98E+03\n",
-      "177000 25 299.93 -2.27E-02 2.15E+01 2.01E+02 4.95E+03\n",
-      "177500 25 300.66 -1.08E-01 2.15E+01 1.97E+02 4.94E+03\n",
-      "178000 25 299.74 -1.70E-02 2.14E+01 1.98E+02 4.93E+03\n",
-      "178500 25 300.33 -4.81E-02 2.15E+01 1.98E+02 4.94E+03\n",
-      "179000 25 298.13 7.47E-02 2.13E+01 2.23E+02 4.97E+03\n",
-      "179500 25 301.49 -1.28E-01 2.16E+01 2.09E+02 4.89E+03\n",
-      "180000 25 299.71 -2.18E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "180500 25 301.92 -1.97E-01 2.16E+01 2.11E+02 4.96E+03\n",
-      "181000 25 299.39 -1.34E-02 2.14E+01 2.22E+02 4.96E+03\n",
-      "181500 25 300.0 -3.20E-02 2.15E+01 2.01E+02 4.94E+03\n",
-      "182000 25 301.04 -1.71E-01 2.15E+01 2.00E+02 4.94E+03\n",
-      "182500 25 299.45 -2.28E-02 2.14E+01 1.97E+02 4.97E+03\n",
-      "183000 25 299.85 -1.25E-01 2.15E+01 2.00E+02 4.88E+03\n",
-      "183500 25 299.6 -3.65E-02 2.14E+01 2.02E+02 4.96E+03\n",
-      "184000 25 300.58 -1.07E-01 2.15E+01 1.37E+02 4.87E+03\n",
-      "184500 25 300.62 -6.91E-02 2.15E+01 2.00E+02 4.90E+03\n",
-      "185000 25 299.74 -2.95E-02 2.14E+01 1.98E+02 4.93E+03\n",
-      "185500 25 299.86 -4.04E-02 2.15E+01 1.98E+02 4.94E+03\n",
-      "186000 25 301.1 -1.50E-01 2.15E+01 1.97E+02 4.93E+03\n",
-      "186500 25 301.81 -1.87E-01 2.16E+01 1.99E+02 4.92E+03\n",
-      "187000 25 299.96 -1.76E-01 2.15E+01 1.98E+02 4.91E+03\n",
-      "187500 25 301.3 -1.77E-01 2.16E+01 2.01E+02 4.92E+03\n",
-      "188000 25 299.68 -1.13E-02 2.14E+01 1.99E+02 4.91E+03\n",
-      "188500 25 299.65 -2.78E-02 2.14E+01 2.01E+02 4.93E+03\n",
-      "189000 25 301.19 -1.18E-01 2.15E+01 1.99E+02 4.95E+03\n",
-      "189500 25 301.05 -1.11E-01 2.15E+01 2.00E+02 4.92E+03\n",
-      "190000 25 300.58 -9.29E-02 2.15E+01 1.98E+02 4.94E+03\n",
-      "190500 25 300.01 -5.52E-02 2.15E+01 2.09E+02 4.94E+03\n",
-      "191000 25 299.77 -1.62E-02 2.14E+01 1.97E+02 4.96E+03\n",
-      "191500 25 300.85 -1.08E-01 2.15E+01 1.99E+02 4.94E+03\n",
-      "192000 25 299.77 -3.62E-02 2.14E+01 1.97E+02 4.95E+03\n",
-      "192500 25 299.57 -4.57E-02 2.14E+01 1.97E+02 4.96E+03\n",
-      "193000 25 299.64 -1.85E-02 2.14E+01 1.98E+02 4.94E+03\n",
-      "193500 25 300.99 -1.09E-01 2.15E+01 2.00E+02 4.91E+03\n",
-      "194000 25 300.59 -6.44E-02 2.15E+01 2.16E+02 4.80E+03\n",
-      "194500 25 299.86 -6.15E-02 2.15E+01 2.02E+02 4.86E+03\n",
-      "195000 25 301.75 -1.92E-01 2.16E+01 2.02E+02 4.81E+03\n",
-      "195500 25 299.21 -2.72E-02 2.14E+01 2.03E+02 4.88E+03\n",
-      "196000 25 301.17 -1.13E-01 2.15E+01 2.12E+02 4.78E+03\n",
-      "196500 25 299.5 -1.63E-02 2.14E+01 2.00E+02 4.89E+03\n",
-      "197000 25 299.04 -2.41E-02 2.14E+01 2.01E+02 4.86E+03\n",
-      "197500 25 300.2 -1.10E-01 2.15E+01 1.99E+02 4.91E+03\n",
-      "198000 25 300.06 -5.75E-02 2.15E+01 2.08E+02 4.93E+03\n",
-      "198500 25 299.03 3.47E-02 2.14E+01 2.15E+02 4.92E+03\n",
-      "199000 25 299.56 -1.35E-02 2.14E+01 1.98E+02 4.93E+03\n",
-      "199500 25 299.5 -2.71E-02 2.14E+01 1.97E+02 4.96E+03\n",
-      "200000 25 299.8 -2.04E-02 2.14E+01 1.99E+02 4.96E+03\n"
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "sys.path.append(\"../../molecular-simulation/\")\n",
-    "from main import MolecularDynamics\n",
-    "\n",
-    "MolecularDynamics(number_atoms=25,\n",
-    "                    Lx=12,\n",
-    "                    maximum_steps=200000,\n",
-    "                    dimensions= 3,\n",
-    "                    desired_temperature=300,\n",
-    "                    desired_pressure=200,\n",
-    "                    tau_temp=100,\n",
-    "                    tau_press=1000,\n",
-    "                    seed=41982,\n",
-    "                    thermo=500,\n",
-    "                    dump=500,\n",
-    "                    ).run()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/benchmark/python_mu2_1.7nm3_300K_GCMC/run.ipynb b/benchmark/python_mu2_1.7nm3_300K_GCMC/run.ipynb
deleted file mode 100644
index 1fd24b6..0000000
--- a/benchmark/python_mu2_1.7nm3_300K_GCMC/run.ipynb
+++ /dev/null
@@ -1,1263 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "step N temp epot ekin press vol\n",
-      "0 24 94.07 -1.36E-02 6.45E+00 3.68E+01 8.00E+03\n",
-      "500 9 270.45 -7.36E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "1000 9 270.45 -2.00E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "1500 10 240.4 -2.12E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "2000 10 240.4 -3.82E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "2500 10 240.4 -1.60E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "3000 11 216.36 -7.60E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "3500 6 432.72 -2.58E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "4000 17 135.23 -6.69E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "4500 6 432.72 -8.38E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "5000 6 432.72 -1.53E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "5500 13 180.3 -1.99E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "6000 7 360.6 -5.68E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "6500 13 180.3 -1.30E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "7000 17 135.23 -1.31E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "7500 12 196.69 -5.73E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "8000 9 270.45 -4.82E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "8500 9 270.45 -3.86E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "9000 12 196.69 -4.57E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "9500 9 270.45 -1.62E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "10000 10 240.4 -1.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "10500 7 360.6 -1.12E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "11000 9 270.45 -1.71E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "11500 14 166.43 -9.31E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "12000 12 196.69 -1.97E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "12500 15 154.54 -8.26E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "13000 10 240.4 -2.32E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "13500 7 360.6 -1.07E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "14000 8 309.09 -2.14E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "14500 6 432.72 -1.00E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "15000 14 166.43 -9.60E-02 6.45E+00 3.59E+01 8.00E+03\n",
-      "15500 5 540.91 -4.83E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "16000 8 309.09 -7.15E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "16500 9 270.45 -2.68E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "17000 9 270.45 -1.17E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "17500 8 309.09 -4.61E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "18000 12 196.69 -7.87E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "18500 11 216.36 -2.37E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "19000 10 240.4 -2.27E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "19500 7 360.6 -1.84E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "20000 12 196.69 -1.31E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "20500 6 432.72 -3.94E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "21000 14 166.43 -5.68E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "21500 10 240.4 -1.28E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "22000 2 2163.62 -6.66E-07 6.45E+00 3.69E+01 8.00E+03\n",
-      "22500 11 216.36 -8.45E-02 6.45E+00 3.87E+01 8.00E+03\n",
-      "23000 7 360.6 -7.54E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "23500 9 270.45 -5.81E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "24000 10 240.4 -2.51E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "24500 9 270.45 -5.21E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "25000 15 154.54 -6.47E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "25500 11 216.36 -2.43E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "26000 11 216.36 -1.14E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "26500 6 432.72 -1.59E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "27000 4 721.21 -2.05E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "27500 10 240.4 -6.68E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "28000 8 309.09 -2.09E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "28500 13 180.3 -6.64E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "29000 11 216.36 -1.09E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "29500 5 540.91 -1.86E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "30000 6 432.72 -4.01E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "30500 8 309.09 -3.57E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "31000 16 144.24 -5.77E-02 6.45E+00 4.06E+01 8.00E+03\n",
-      "31500 8 309.09 -5.25E-03 6.45E+00 3.75E+01 8.00E+03\n",
-      "32000 2 2163.62 -4.88E-07 6.45E+00 3.69E+01 8.00E+03\n",
-      "32500 5 540.91 -5.14E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "33000 13 180.3 -6.71E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "33500 12 196.69 -2.21E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "34000 8 309.09 -1.99E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "34500 6 432.72 -7.04E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "35000 9 270.45 -3.31E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "35500 7 360.6 -2.76E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "36000 9 270.45 -2.74E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "36500 8 309.09 -1.75E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "37000 8 309.09 -4.78E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "37500 5 540.91 -2.17E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "38000 12 196.69 -3.09E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "38500 7 360.6 -2.18E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "39000 7 360.6 -4.70E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "39500 5 540.91 -1.99E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "40000 14 166.43 -1.41E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "40500 10 240.4 -7.40E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "41000 10 240.4 -4.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "41500 9 270.45 -1.75E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "42000 11 216.36 -1.56E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "42500 9 270.45 -1.60E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "43000 11 216.36 -1.24E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "43500 10 240.4 -2.12E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "44000 13 180.3 -1.16E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "44500 7 360.6 -4.54E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "45000 12 196.69 -2.31E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "45500 13 180.3 -6.49E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "46000 7 360.6 -2.03E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "46500 9 270.45 -7.06E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "47000 8 309.09 -1.06E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "47500 9 270.45 -7.40E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "48000 9 270.45 -4.39E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "48500 9 270.45 -7.38E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "49000 10 240.4 -2.12E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "49500 17 135.23 -1.11E-02 6.45E+00 3.71E+01 8.00E+03\n",
-      "50000 15 154.54 -2.80E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "50500 11 216.36 -3.93E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "51000 6 432.72 -7.95E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "51500 14 166.43 -5.38E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "52000 11 216.36 -1.25E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "52500 8 309.09 -1.85E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "53000 11 216.36 -2.40E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "53500 10 240.4 -2.03E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "54000 3 1081.81 -6.10E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "54500 11 216.36 -3.47E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "55000 11 216.36 -2.31E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "55500 7 360.6 -6.80E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "56000 8 309.09 -3.16E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "56500 5 540.91 -1.14E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "57000 11 216.36 -3.49E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "57500 8 309.09 -1.04E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "58000 5 540.91 -1.40E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "58500 8 309.09 -2.23E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "59000 11 216.36 -5.60E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "59500 6 432.72 -3.79E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "60000 9 270.45 -3.64E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "60500 7 360.6 -4.82E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "61000 10 240.4 -1.97E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "61500 13 180.3 -6.15E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "62000 6 432.72 -2.35E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "62500 4 721.21 -7.09E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "63000 11 216.36 -2.34E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "63500 9 270.45 -7.18E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "64000 10 240.4 -1.68E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "64500 8 309.09 -9.82E-02 6.45E+00 3.74E+01 8.00E+03\n",
-      "65000 15 154.54 -1.91E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "65500 10 240.4 -1.95E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "66000 9 270.45 -6.95E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "66500 12 196.69 -3.36E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "67000 6 432.72 -1.06E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "67500 5 540.91 -2.47E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "68000 5 540.91 -2.64E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "68500 10 240.4 -2.36E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "69000 11 216.36 -7.95E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "69500 11 216.36 -1.81E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "70000 13 180.3 -1.44E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "70500 9 270.45 -1.61E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "71000 7 360.6 -4.42E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "71500 7 360.6 -7.25E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "72000 9 270.45 -1.99E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "72500 8 309.09 -1.50E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "73000 9 270.45 -2.67E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "73500 14 166.43 -2.38E-02 6.45E+00 4.02E+01 8.00E+03\n",
-      "74000 9 270.45 -5.29E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "74500 13 180.3 -3.82E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "75000 11 216.36 -1.68E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "75500 12 196.69 -2.55E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "76000 8 309.09 -1.07E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "76500 11 216.36 -1.08E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "77000 13 180.3 -5.91E-02 6.45E+00 3.61E+01 8.00E+03\n",
-      "77500 14 166.43 -5.79E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "78000 14 166.43 -4.00E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "78500 12 196.69 -4.62E-03 6.45E+00 3.72E+01 8.00E+03\n",
-      "79000 13 180.3 -9.17E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "79500 9 270.45 -3.27E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "80000 7 360.6 -7.36E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "80500 12 196.69 -2.35E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "81000 7 360.6 -6.40E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "81500 7 360.6 -1.04E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "82000 11 216.36 -8.37E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "82500 10 240.4 -2.95E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "83000 12 196.69 -1.09E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "83500 10 240.4 -7.88E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "84000 7 360.6 -3.35E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "84500 10 240.4 -1.09E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "85000 8 309.09 -1.11E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "85500 6 432.72 -9.17E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "86000 9 270.45 -1.19E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "86500 10 240.4 -1.64E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "87000 18 127.27 -1.46E-02 6.45E+00 3.82E+01 8.00E+03\n",
-      "87500 9 270.45 -1.37E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "88000 10 240.4 -1.31E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "88500 7 360.6 -1.78E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "89000 7 360.6 -9.35E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "89500 13 180.3 -9.58E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "90000 8 309.09 -1.13E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "90500 9 270.45 -9.30E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "91000 12 196.69 -4.40E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "91500 14 166.43 -2.19E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "92000 13 180.3 -4.81E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "92500 11 216.36 -1.05E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "93000 8 309.09 -4.56E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "93500 7 360.6 -6.01E-02 6.45E+00 4.79E+01 8.00E+03\n",
-      "94000 6 432.72 -2.48E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "94500 9 270.45 -1.29E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "95000 6 432.72 -6.63E-02 6.45E+00 5.25E+01 8.00E+03\n",
-      "95500 18 127.27 -9.91E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "96000 17 135.23 -4.21E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "96500 5 540.91 -6.48E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "97000 7 360.6 -6.71E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "97500 3 1081.81 -2.59E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "98000 11 216.36 -1.44E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "98500 14 166.43 -5.69E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "99000 9 270.45 -1.30E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "99500 7 360.6 -3.19E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "100000 7 360.6 -4.17E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "100500 7 360.6 -2.06E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "101000 11 216.36 -1.29E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "101500 11 216.36 -7.56E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "102000 7 360.6 -4.74E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "102500 3 1081.81 -2.09E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "103000 10 240.4 -2.16E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "103500 12 196.69 -5.60E-02 6.45E+00 4.24E+01 8.00E+03\n",
-      "104000 9 270.45 -7.63E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "104500 6 432.72 -6.22E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "105000 13 180.3 -8.97E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "105500 10 240.4 -2.00E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "106000 12 196.69 -2.92E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "106500 11 216.36 -8.25E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "107000 9 270.45 -4.08E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "107500 10 240.4 -3.65E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "108000 10 240.4 -1.46E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "108500 10 240.4 -1.41E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "109000 13 180.3 -1.08E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "109500 12 196.69 -1.95E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "110000 7 360.6 -8.56E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "110500 10 240.4 -4.80E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "111000 9 270.45 -6.10E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "111500 17 135.23 -6.30E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "112000 15 154.54 -1.72E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "112500 15 154.54 -8.89E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "113000 3 1081.81 -1.36E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "113500 6 432.72 -1.40E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "114000 7 360.6 -1.41E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "114500 10 240.4 -2.37E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "115000 9 270.45 -2.15E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "115500 4 721.21 -1.55E-02 6.45E+00 3.93E+01 8.00E+03\n",
-      "116000 10 240.4 -3.93E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "116500 10 240.4 -1.44E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "117000 14 166.43 -6.26E-03 6.45E+00 3.71E+01 8.00E+03\n",
-      "117500 10 240.4 -7.63E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "118000 13 180.3 -5.44E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "118500 7 360.6 -2.23E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "119000 12 196.69 -1.76E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "119500 9 270.45 -1.22E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "120000 13 180.3 -2.90E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "120500 14 166.43 -1.17E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "121000 14 166.43 -3.36E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "121500 10 240.4 1.31E-01 6.45E+00 5.00E+01 8.00E+03\n",
-      "122000 10 240.4 -5.04E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "122500 12 196.69 -2.31E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "123000 10 240.4 -4.03E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "123500 11 216.36 -8.63E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "124000 9 270.45 1.04E-01 6.45E+00 4.94E+01 8.00E+03\n",
-      "124500 9 270.45 -2.73E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "125000 7 360.6 -2.48E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "125500 10 240.4 -4.09E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "126000 6 432.72 -5.96E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "126500 9 270.45 -5.43E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "127000 10 240.4 -1.18E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "127500 10 240.4 -1.11E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "128000 6 432.72 -9.68E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "128500 6 432.72 -6.51E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "129000 15 154.54 -5.49E-02 6.45E+00 3.61E+01 8.00E+03\n",
-      "129500 11 216.36 -5.58E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "130000 14 166.43 -3.97E-02 6.45E+00 3.63E+01 8.00E+03\n",
-      "130500 12 196.69 -8.03E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "131000 9 270.45 -9.80E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "131500 9 270.45 -3.02E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "132000 14 166.43 -1.14E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "132500 11 216.36 -8.42E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "133000 6 432.72 1.59E-01 6.45E+00 5.12E+01 8.00E+03\n",
-      "133500 8 309.09 -4.00E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "134000 6 432.72 -7.91E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "134500 9 270.45 -5.91E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "135000 6 432.72 -1.12E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "135500 10 240.4 -2.28E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "136000 12 196.69 -1.35E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "136500 7 360.6 -8.94E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "137000 8 309.09 -2.31E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "137500 14 166.43 -5.22E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "138000 9 270.45 -2.79E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "138500 6 432.72 -1.06E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "139000 5 540.91 -1.84E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "139500 11 216.36 -1.15E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "140000 5 540.91 -1.95E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "140500 11 216.36 -1.21E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "141000 14 166.43 -3.00E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "141500 8 309.09 -3.11E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "142000 12 196.69 -9.60E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "142500 13 180.3 -8.74E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "143000 12 196.69 -1.41E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "143500 7 360.6 -1.28E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "144000 8 309.09 -4.21E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "144500 9 270.45 -1.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "145000 7 360.6 -1.40E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "145500 9 270.45 -1.18E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "146000 3 1081.81 -9.90E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "146500 13 180.3 -1.31E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "147000 14 166.43 -6.63E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "147500 10 240.4 -2.11E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "148000 7 360.6 -7.97E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "148500 14 166.43 -2.89E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "149000 8 309.09 -7.40E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "149500 20 113.87 -2.07E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "150000 6 432.72 -4.30E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "150500 13 180.3 -1.16E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "151000 10 240.4 -2.28E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "151500 6 432.72 -1.55E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "152000 3 1081.81 -8.66E-07 6.45E+00 3.69E+01 8.00E+03\n",
-      "152500 11 216.36 -1.37E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "153000 6 432.72 -4.01E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "153500 13 180.3 -1.01E-01 6.45E+00 3.68E+01 8.00E+03\n",
-      "154000 8 309.09 -1.60E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "154500 9 270.45 -3.19E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "155000 15 154.54 -1.52E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "155500 13 180.3 -1.08E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "156000 10 240.4 -9.07E-02 6.45E+00 3.61E+01 8.00E+03\n",
-      "156500 10 240.4 -1.28E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "157000 9 270.45 -3.90E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "157500 9 270.45 -2.00E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "158000 5 540.91 -5.22E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "158500 9 270.45 -5.39E-03 6.45E+00 3.72E+01 8.00E+03\n",
-      "159000 12 196.69 -7.39E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "159500 3 1081.81 -5.76E-07 6.45E+00 3.69E+01 8.00E+03\n",
-      "160000 5 540.91 -6.21E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "160500 13 180.3 -6.24E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "161000 14 166.43 -7.54E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "161500 1 inf 0.00E+00 6.45E+00 NAN 8.00E+03\n",
-      "162000 5 540.91 -5.10E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "162500 7 360.6 -9.85E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "163000 15 154.54 -7.01E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "163500 9 270.45 -3.52E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "164000 9 270.45 -1.88E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "164500 14 166.43 -2.18E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "165000 5 540.91 -2.16E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "165500 10 240.4 -1.60E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "166000 11 216.36 -1.04E-01 6.45E+00 3.64E+01 8.00E+03\n",
-      "166500 6 432.72 -2.18E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "167000 11 216.36 -2.19E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "167500 14 166.43 -3.60E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "168000 8 309.09 -4.66E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "168500 12 196.69 -2.35E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "169000 5 540.91 -8.44E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "169500 7 360.6 -5.19E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "170000 12 196.69 -3.09E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "170500 8 309.09 -2.46E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "171000 5 540.91 -1.99E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "171500 8 309.09 -8.63E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "172000 8 309.09 -7.48E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "172500 8 309.09 -2.43E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "173000 8 309.09 -1.31E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "173500 14 166.43 -5.40E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "174000 12 196.69 -9.96E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "174500 11 216.36 -1.32E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "175000 6 432.72 -4.43E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "175500 8 309.09 -3.35E-02 6.45E+00 3.63E+01 8.00E+03\n",
-      "176000 10 240.4 -8.68E-02 6.45E+00 3.56E+01 8.00E+03\n",
-      "176500 13 180.3 -4.56E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "177000 9 270.45 -3.04E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "177500 13 180.3 -1.01E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "178000 5 540.91 -3.68E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "178500 10 240.4 -1.79E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "179000 9 270.45 -8.23E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "179500 12 196.69 -1.00E-01 6.45E+00 3.66E+01 8.00E+03\n",
-      "180000 8 309.09 -3.36E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "180500 6 432.72 -9.46E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "181000 7 360.6 -4.32E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "181500 9 270.45 -1.42E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "182000 13 180.3 -8.99E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "182500 14 166.43 -7.76E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "183000 9 270.45 -2.22E-02 6.45E+00 3.89E+01 8.00E+03\n",
-      "183500 9 270.45 -3.32E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "184000 5 540.91 -2.02E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "184500 8 309.09 -2.21E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "185000 8 309.09 -9.33E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "185500 4 721.21 -9.64E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "186000 14 166.43 -8.17E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "186500 4 721.21 -3.40E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "187000 7 360.6 -8.40E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "187500 7 360.6 -1.41E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "188000 9 270.45 -1.37E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "188500 9 270.45 -2.11E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "189000 9 270.45 -4.33E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "189500 8 309.09 -2.41E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "190000 9 270.45 -1.28E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "190500 9 270.45 -1.29E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "191000 4 721.21 -3.01E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "191500 10 240.4 -4.83E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "192000 11 216.36 -3.42E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "192500 11 216.36 -1.33E-01 6.45E+00 3.59E+01 8.00E+03\n",
-      "193000 9 270.45 -1.82E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "193500 11 216.36 -1.08E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "194000 10 240.4 -4.79E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "194500 12 196.69 -7.57E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "195000 7 360.6 -6.95E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "195500 12 196.69 -5.82E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "196000 15 154.54 -1.82E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "196500 16 144.24 -1.42E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "197000 11 216.36 -4.11E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "197500 9 270.45 -7.93E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "198000 9 270.45 -5.40E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "198500 7 360.6 -3.13E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "199000 16 144.24 -6.58E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "199500 8 309.09 -1.61E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "200000 9 270.45 -6.23E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "200500 6 432.72 -3.58E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "201000 6 432.72 -1.63E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "201500 9 270.45 -1.76E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "202000 7 360.6 -1.51E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "202500 12 196.69 -8.59E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "203000 9 270.45 -4.58E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "203500 9 270.45 -5.48E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "204000 13 180.3 -9.75E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "204500 11 216.36 -8.02E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "205000 10 240.4 -1.06E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "205500 14 166.43 -1.03E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "206000 8 309.09 -2.31E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "206500 9 270.45 -1.70E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "207000 8 309.09 -4.17E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "207500 10 240.4 -4.52E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "208000 9 270.45 -2.10E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "208500 5 540.91 -2.94E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "209000 12 196.69 -1.92E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "209500 11 216.36 -7.12E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "210000 5 540.91 -1.50E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "210500 13 180.3 -6.37E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "211000 14 166.43 -8.42E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "211500 3 1081.81 -1.60E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "212000 11 216.36 -1.56E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "212500 12 196.69 -1.19E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "213000 8 309.09 -1.26E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "213500 8 309.09 -9.98E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "214000 6 432.72 -4.38E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "214500 7 360.6 -7.47E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "215000 5 540.91 -1.05E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "215500 10 240.4 -1.88E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "216000 10 240.4 -8.26E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "216500 12 196.69 -2.57E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "217000 9 270.45 -2.22E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "217500 10 240.4 -8.39E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "218000 7 360.6 -3.63E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "218500 9 270.45 -6.85E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "219000 9 270.45 -5.74E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "219500 15 154.54 -4.13E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "220000 9 270.45 -7.57E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "220500 12 196.69 -4.09E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "221000 6 432.72 -1.63E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "221500 13 180.3 -1.97E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "222000 3 1081.81 -8.94E-07 6.45E+00 3.69E+01 8.00E+03\n",
-      "222500 5 540.91 -2.85E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "223000 4 721.21 -2.41E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "223500 9 270.45 -1.52E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "224000 15 154.54 -1.04E-02 6.45E+00 3.77E+01 8.00E+03\n",
-      "224500 5 540.91 -1.22E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "225000 14 166.43 -5.27E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "225500 8 309.09 -1.97E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "226000 9 270.45 -4.61E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "226500 11 216.36 -2.84E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "227000 10 240.4 -2.33E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "227500 11 216.36 -2.69E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "228000 11 216.36 -1.86E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "228500 10 240.4 -8.09E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "229000 5 540.91 -1.31E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "229500 7 360.6 -7.31E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "230000 14 166.43 -7.93E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "230500 8 309.09 -1.38E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "231000 13 180.3 -3.73E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "231500 6 432.72 -2.64E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "232000 6 432.72 -5.02E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "232500 6 432.72 -3.56E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "233000 17 135.23 -1.98E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "233500 6 432.72 -3.24E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "234000 8 309.09 -6.32E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "234500 15 154.54 -7.52E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "235000 10 240.4 -9.60E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "235500 8 309.09 -2.50E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "236000 10 240.4 -2.17E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "236500 13 180.3 -6.04E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "237000 12 196.69 -6.22E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "237500 9 270.45 -9.75E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "238000 6 432.72 -1.34E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "238500 16 144.24 -7.64E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "239000 8 309.09 -7.74E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "239500 13 180.3 -1.08E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "240000 7 360.6 -1.66E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "240500 7 360.6 -2.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "241000 13 180.3 -4.32E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "241500 8 309.09 -4.35E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "242000 7 360.6 -1.15E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "242500 7 360.6 -3.82E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "243000 11 216.36 -1.24E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "243500 20 113.87 -3.51E-02 6.45E+00 3.72E+01 8.00E+03\n",
-      "244000 10 240.4 -1.16E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "244500 15 154.54 -4.34E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "245000 13 180.3 -3.71E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "245500 12 196.69 -1.26E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "246000 18 127.27 -6.18E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "246500 8 309.09 -8.24E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "247000 7 360.6 -1.02E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "247500 12 196.69 -3.57E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "248000 12 196.69 -5.99E-03 6.45E+00 3.76E+01 8.00E+03\n",
-      "248500 4 721.21 -8.49E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "249000 11 216.36 -3.90E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "249500 10 240.4 -1.16E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "250000 7 360.6 -1.70E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "250500 8 309.09 -7.35E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "251000 13 180.3 -1.17E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "251500 13 180.3 -3.59E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "252000 8 309.09 -5.58E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "252500 16 144.24 -5.86E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "253000 8 309.09 -1.00E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "253500 9 270.45 -6.28E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "254000 4 721.21 -1.67E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "254500 8 309.09 -3.86E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "255000 8 309.09 -1.09E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "255500 15 154.54 -1.15E-01 6.45E+00 4.18E+01 8.00E+03\n",
-      "256000 13 180.3 -1.01E-01 6.45E+00 3.73E+01 8.00E+03\n",
-      "256500 9 270.45 -3.52E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "257000 11 216.36 -1.42E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "257500 9 270.45 -1.17E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "258000 11 216.36 -9.05E-02 6.45E+00 4.74E+01 8.00E+03\n",
-      "258500 8 309.09 -1.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "259000 8 309.09 -9.67E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "259500 7 360.6 -9.06E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "260000 10 240.4 -2.81E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "260500 9 270.45 -2.72E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "261000 9 270.45 -2.24E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "261500 7 360.6 -6.71E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "262000 8 309.09 -1.83E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "262500 7 360.6 -4.24E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "263000 4 721.21 -1.44E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "263500 9 270.45 -4.37E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "264000 10 240.4 -1.18E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "264500 9 270.45 -2.10E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "265000 8 309.09 -2.60E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "265500 16 144.24 -1.81E-02 6.45E+00 3.79E+01 8.00E+03\n",
-      "266000 5 540.91 -2.94E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "266500 8 309.09 -6.72E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "267000 12 196.69 -1.16E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "267500 10 240.4 -5.43E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "268000 12 196.69 -2.80E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "268500 9 270.45 -3.98E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "269000 13 180.3 -6.11E-03 6.45E+00 3.72E+01 8.00E+03\n",
-      "269500 8 309.09 -5.79E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "270000 9 270.45 -4.76E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "270500 13 180.3 -9.23E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "271000 13 180.3 -4.41E-02 6.45E+00 3.61E+01 8.00E+03\n",
-      "271500 8 309.09 -1.55E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "272000 10 240.4 -9.65E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "272500 6 432.72 -2.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "273000 11 216.36 -4.95E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "273500 4 721.21 -3.77E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "274000 8 309.09 -2.75E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "274500 13 180.3 -2.00E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "275000 6 432.72 -1.22E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "275500 11 216.36 -5.38E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "276000 13 180.3 -2.11E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "276500 11 216.36 -7.41E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "277000 10 240.4 -3.22E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "277500 10 240.4 -2.47E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "278000 7 360.6 -2.44E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "278500 13 180.3 -2.90E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "279000 6 432.72 -5.10E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "279500 8 309.09 -1.05E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "280000 16 144.24 -3.82E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "280500 11 216.36 -1.94E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "281000 11 216.36 -6.22E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "281500 5 540.91 -1.37E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "282000 7 360.6 -9.00E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "282500 10 240.4 -1.41E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "283000 11 216.36 -4.27E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "283500 2 2163.62 -3.91E-07 6.45E+00 3.69E+01 8.00E+03\n",
-      "284000 10 240.4 -7.33E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "284500 7 360.6 -3.46E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "285000 3 1081.81 -1.54E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "285500 9 270.45 -1.50E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "286000 11 216.36 -1.74E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "286500 9 270.45 -1.28E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "287000 8 309.09 -1.02E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "287500 9 270.45 -1.29E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "288000 6 432.72 -2.62E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "288500 12 196.69 -1.56E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "289000 6 432.72 -3.20E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "289500 9 270.45 -1.47E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "290000 10 240.4 -4.79E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "290500 10 240.4 -5.01E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "291000 8 309.09 -2.84E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "291500 6 432.72 -3.41E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "292000 7 360.6 -2.04E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "292500 7 360.6 -7.63E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "293000 7 360.6 -1.01E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "293500 7 360.6 -2.44E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "294000 9 270.45 -1.71E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "294500 8 309.09 -6.25E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "295000 7 360.6 -2.18E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "295500 9 270.45 -5.14E-02 6.45E+00 4.10E+01 8.00E+03\n",
-      "296000 14 166.43 -4.26E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "296500 8 309.09 -7.74E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "297000 13 180.3 -1.06E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "297500 13 180.3 -3.02E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "298000 14 166.43 -7.78E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "298500 10 240.4 -3.71E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "299000 8 309.09 -1.26E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "299500 8 309.09 -4.04E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "300000 13 180.3 -4.50E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "300500 7 360.6 -2.55E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "301000 13 180.3 -9.96E-02 6.45E+00 3.72E+01 8.00E+03\n",
-      "301500 11 216.36 -1.38E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "302000 9 270.45 -1.79E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "302500 14 166.43 -1.30E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "303000 12 196.69 -1.39E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "303500 9 270.45 -6.76E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "304000 11 216.36 -1.92E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "304500 5 540.91 -2.16E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "305000 7 360.6 -1.54E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "305500 11 216.36 -2.91E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "306000 6 432.72 -1.11E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "306500 14 166.43 -7.93E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "307000 10 240.4 -7.21E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "307500 10 240.4 -4.60E-02 6.45E+00 3.63E+01 8.00E+03\n",
-      "308000 11 216.36 -3.51E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "308500 8 309.09 -2.24E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "309000 10 240.4 -5.72E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "309500 6 432.72 -1.59E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "310000 11 216.36 -2.42E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "310500 11 216.36 3.70E-01 6.45E+00 7.33E+01 8.00E+03\n",
-      "311000 9 270.45 -3.95E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "311500 16 144.24 -1.54E-02 6.45E+00 3.80E+01 8.00E+03\n",
-      "312000 9 270.45 -7.89E-03 6.45E+00 3.72E+01 8.00E+03\n",
-      "312500 13 180.3 -4.32E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "313000 11 216.36 -4.33E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "313500 8 309.09 -2.26E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "314000 9 270.45 -4.64E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "314500 13 180.3 -1.80E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "315000 9 270.45 -9.92E-02 6.45E+00 3.97E+01 8.00E+03\n",
-      "315500 10 240.4 -2.76E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "316000 5 540.91 -1.66E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "316500 6 432.72 -2.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "317000 9 270.45 -4.10E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "317500 11 216.36 -4.57E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "318000 6 432.72 -7.06E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "318500 7 360.6 -5.88E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "319000 7 360.6 -6.93E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "319500 11 216.36 -4.75E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "320000 8 309.09 -4.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "320500 9 270.45 -2.08E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "321000 16 144.24 -9.59E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "321500 10 240.4 -1.53E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "322000 12 196.69 -1.23E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "322500 11 216.36 -4.32E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "323000 8 309.09 -2.18E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "323500 10 240.4 -2.11E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "324000 9 270.45 -9.87E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "324500 7 360.6 -5.30E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "325000 13 180.3 -5.51E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "325500 12 196.69 -1.44E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "326000 7 360.6 -1.08E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "326500 9 270.45 -2.26E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "327000 7 360.6 -1.02E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "327500 2 2163.62 -3.41E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "328000 6 432.72 -2.52E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "328500 4 721.21 -9.67E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "329000 2 2163.62 -3.97E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "329500 9 270.45 -1.38E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "330000 4 721.21 -6.84E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "330500 10 240.4 -2.60E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "331000 10 240.4 -1.58E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "331500 8 309.09 -8.09E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "332000 8 309.09 -2.25E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "332500 10 240.4 -8.35E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "333000 9 270.45 -1.04E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "333500 5 540.91 -3.72E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "334000 6 432.72 -1.61E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "334500 11 216.36 -1.85E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "335000 16 144.24 -1.70E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "335500 16 144.24 -1.49E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "336000 10 240.4 -4.71E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "336500 20 113.87 -2.81E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "337000 7 360.6 -5.37E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "337500 10 240.4 -7.63E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "338000 14 166.43 -1.50E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "338500 16 144.24 -3.54E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "339000 8 309.09 -1.65E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "339500 6 432.72 -1.84E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "340000 11 216.36 -6.04E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "340500 5 540.91 -1.52E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "341000 8 309.09 -7.12E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "341500 9 270.45 -8.20E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "342000 11 216.36 -1.69E-02 6.45E+00 3.69E+01 8.00E+03\n",
-      "342500 11 216.36 -9.00E-03 6.45E+00 3.80E+01 8.00E+03\n",
-      "343000 7 360.6 -3.25E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "343500 11 216.36 -1.77E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "344000 7 360.6 -1.43E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "344500 11 216.36 -4.01E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "345000 8 309.09 -7.53E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "345500 14 166.43 -4.70E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "346000 7 360.6 -7.76E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "346500 6 432.72 -2.40E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "347000 17 135.23 -3.51E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "347500 13 180.3 -2.06E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "348000 8 309.09 -9.67E-02 6.45E+00 3.76E+01 8.00E+03\n",
-      "348500 4 721.21 -1.22E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "349000 8 309.09 -9.82E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "349500 11 216.36 -7.16E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "350000 9 270.45 -2.99E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "350500 9 270.45 -1.33E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "351000 9 270.45 -6.45E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "351500 7 360.6 -5.93E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "352000 7 360.6 -6.03E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "352500 12 196.69 -1.47E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "353000 10 240.4 -5.76E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "353500 6 432.72 -8.18E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "354000 7 360.6 -7.90E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "354500 5 540.91 -3.43E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "355000 9 270.45 -4.18E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "355500 8 309.09 -3.60E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "356000 10 240.4 -2.00E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "356500 10 240.4 -1.21E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "357000 13 180.3 -1.44E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "357500 6 432.72 -8.20E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "358000 8 309.09 -2.81E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "358500 11 216.36 -2.43E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "359000 10 240.4 -1.23E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "359500 12 196.69 -2.09E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "360000 12 196.69 -2.79E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "360500 10 240.4 -1.04E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "361000 10 240.4 -3.06E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "361500 11 216.36 -8.05E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "362000 7 360.6 -9.80E-02 6.45E+00 3.74E+01 8.00E+03\n",
-      "362500 9 270.45 -1.13E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "363000 11 216.36 -1.62E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "363500 10 240.4 -4.93E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "364000 11 216.36 2.33E-02 6.45E+00 4.76E+01 8.00E+03\n",
-      "364500 8 309.09 -3.16E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "365000 4 721.21 -2.84E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "365500 11 216.36 -8.03E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "366000 13 180.3 -6.73E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "366500 6 432.72 -2.73E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "367000 9 270.45 -4.20E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "367500 8 309.09 -4.38E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "368000 12 196.69 -6.85E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "368500 10 240.4 -8.66E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "369000 7 360.6 -6.01E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "369500 7 360.6 -6.01E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "370000 3 1081.81 -2.52E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "370500 6 432.72 -5.82E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "371000 11 216.36 -2.71E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "371500 9 270.45 -7.47E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "372000 11 216.36 -3.79E-02 6.45E+00 3.63E+01 8.00E+03\n",
-      "372500 6 432.72 -2.22E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "373000 9 270.45 -1.08E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "373500 9 270.45 -5.53E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "374000 5 540.91 -2.07E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "374500 9 270.45 -2.76E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "375000 4 721.21 -3.37E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "375500 6 432.72 -1.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "376000 8 309.09 -1.66E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "376500 6 432.72 -7.73E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "377000 12 196.69 -1.14E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "377500 9 270.45 -2.39E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "378000 10 240.4 -2.47E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "378500 9 270.45 -4.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "379000 12 196.69 -1.51E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "379500 9 270.45 -3.17E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "380000 9 270.45 -1.72E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "380500 10 240.4 -6.27E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "381000 16 144.24 -3.65E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "381500 9 270.45 -1.17E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "382000 8 309.09 -5.47E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "382500 9 270.45 -1.59E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "383000 5 540.91 -1.46E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "383500 6 432.72 -2.64E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "384000 6 432.72 -3.92E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "384500 6 432.72 -2.13E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "385000 11 216.36 -7.99E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "385500 14 166.43 -1.34E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "386000 11 216.36 -7.30E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "386500 12 196.69 -2.26E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "387000 10 240.4 -2.11E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "387500 4 721.21 -3.24E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "388000 6 432.72 -8.41E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "388500 8 309.09 -5.38E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "389000 13 180.3 -5.00E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "389500 11 216.36 -5.65E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "390000 12 196.69 -2.94E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "390500 10 240.4 -6.06E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "391000 12 196.69 -6.50E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "391500 8 309.09 -3.85E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "392000 10 240.4 -6.57E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "392500 15 154.54 -1.66E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "393000 7 360.6 -2.28E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "393500 9 270.45 -4.41E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "394000 8 309.09 -2.20E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "394500 6 432.72 -5.01E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "395000 3 1081.81 -9.65E-07 6.45E+00 3.69E+01 8.00E+03\n",
-      "395500 7 360.6 -7.40E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "396000 13 180.3 -2.73E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "396500 10 240.4 -2.18E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "397000 8 309.09 -1.29E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "397500 7 360.6 -3.24E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "398000 10 240.4 -2.45E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "398500 8 309.09 -2.39E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "399000 8 309.09 -2.49E-02 6.45E+00 4.05E+01 8.00E+03\n",
-      "399500 6 432.72 -9.48E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "400000 7 360.6 -1.66E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "400500 11 216.36 -3.03E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "401000 10 240.4 -4.22E-02 6.45E+00 4.15E+01 8.00E+03\n",
-      "401500 7 360.6 -9.45E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "402000 9 270.45 -7.06E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "402500 12 196.69 -4.81E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "403000 9 270.45 -2.26E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "403500 8 309.09 -1.24E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "404000 10 240.4 -1.48E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "404500 6 432.72 -2.89E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "405000 8 309.09 -1.33E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "405500 10 240.4 -4.94E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "406000 12 196.69 -1.80E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "406500 12 196.69 -2.35E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "407000 7 360.6 -6.55E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "407500 7 360.6 -1.27E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "408000 10 240.4 -9.74E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "408500 8 309.09 -2.84E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "409000 13 180.3 -5.82E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "409500 9 270.45 -5.64E-02 6.45E+00 3.61E+01 8.00E+03\n",
-      "410000 10 240.4 -2.54E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "410500 7 360.6 -3.25E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "411000 9 270.45 -2.54E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "411500 11 216.36 -2.87E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "412000 11 216.36 -6.06E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "412500 9 270.45 -3.19E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "413000 5 540.91 -8.78E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "413500 11 216.36 -3.24E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "414000 6 432.72 -1.89E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "414500 6 432.72 -8.75E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "415000 8 309.09 -4.58E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "415500 8 309.09 -3.01E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "416000 13 180.3 -9.49E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "416500 8 309.09 -6.29E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "417000 9 270.45 -1.80E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "417500 9 270.45 -6.83E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "418000 12 196.69 -5.58E-03 6.45E+00 3.78E+01 8.00E+03\n",
-      "418500 9 270.45 -1.60E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "419000 11 216.36 -2.26E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "419500 9 270.45 -7.95E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "420000 8 309.09 -5.73E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "420500 9 270.45 -2.01E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "421000 7 360.6 -9.35E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "421500 13 180.3 -3.64E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "422000 5 540.91 -1.71E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "422500 11 216.36 -1.87E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "423000 10 240.4 -3.90E-02 6.45E+00 4.17E+01 8.00E+03\n",
-      "423500 7 360.6 -5.82E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "424000 9 270.45 -1.37E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "424500 11 216.36 -9.17E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "425000 5 540.91 -1.08E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "425500 11 216.36 -4.44E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "426000 13 180.3 -1.32E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "426500 6 432.72 -1.07E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "427000 12 196.69 -1.01E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "427500 9 270.45 -5.84E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "428000 12 196.69 -9.52E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "428500 16 144.24 -1.64E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "429000 8 309.09 -2.62E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "429500 10 240.4 -9.08E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "430000 9 270.45 -4.61E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "430500 8 309.09 -1.05E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "431000 11 216.36 -1.15E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "431500 6 432.72 -7.44E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "432000 7 360.6 -4.55E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "432500 8 309.09 -5.95E-02 6.45E+00 4.05E+01 8.00E+03\n",
-      "433000 13 180.3 -1.98E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "433500 12 196.69 -1.99E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "434000 10 240.4 -6.93E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "434500 7 360.6 -3.33E-03 6.45E+00 3.71E+01 8.00E+03\n",
-      "435000 2 2163.62 -5.07E-07 6.45E+00 3.69E+01 8.00E+03\n",
-      "435500 12 196.69 -2.41E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "436000 14 166.43 -4.43E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "436500 10 240.4 -3.90E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "437000 16 144.24 -9.91E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "437500 8 309.09 -3.57E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "438000 8 309.09 -9.16E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "438500 3 1081.81 -2.42E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "439000 10 240.4 -8.82E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "439500 6 432.72 -4.92E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "440000 6 432.72 -8.22E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "440500 10 240.4 -3.16E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "441000 10 240.4 -2.24E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "441500 8 309.09 -3.11E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "442000 7 360.6 -1.18E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "442500 6 432.72 -3.45E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "443000 18 127.27 -1.86E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "443500 11 216.36 -4.98E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "444000 12 196.69 -2.55E-02 6.45E+00 3.87E+01 8.00E+03\n",
-      "444500 5 540.91 -5.60E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "445000 6 432.72 -3.95E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "445500 8 309.09 -6.27E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "446000 11 216.36 -8.79E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "446500 9 270.45 -2.92E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "447000 10 240.4 -4.08E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "447500 10 240.4 -2.03E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "448000 8 309.09 -6.39E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "448500 9 270.45 -1.26E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "449000 12 196.69 -4.74E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "449500 9 270.45 -7.47E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "450000 6 432.72 -3.57E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "450500 4 721.21 -5.28E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "451000 4 721.21 -4.50E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "451500 11 216.36 -2.57E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "452000 8 309.09 -8.20E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "452500 5 540.91 -3.96E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "453000 12 196.69 -2.35E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "453500 7 360.6 -6.98E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "454000 10 240.4 -1.81E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "454500 13 180.3 -1.24E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "455000 9 270.45 -1.47E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "455500 11 216.36 -1.57E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "456000 6 432.72 -1.76E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "456500 7 360.6 -5.15E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "457000 8 309.09 -5.97E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "457500 9 270.45 -1.20E-02 6.45E+00 3.69E+01 8.00E+03\n",
-      "458000 11 216.36 -6.01E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "458500 11 216.36 -2.06E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "459000 14 166.43 -1.20E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "459500 12 196.69 -7.34E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "460000 10 240.4 -1.92E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "460500 8 309.09 -2.25E-03 6.45E+00 3.71E+01 8.00E+03\n",
-      "461000 9 270.45 -4.93E-02 6.45E+00 3.61E+01 8.00E+03\n",
-      "461500 15 154.54 -1.13E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "462000 6 432.72 -2.07E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "462500 11 216.36 -2.53E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "463000 10 240.4 -6.51E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "463500 12 196.69 -1.76E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "464000 7 360.6 -9.53E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "464500 13 180.3 -3.13E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "465000 11 216.36 -1.18E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "465500 10 240.4 -1.48E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "466000 5 540.91 -1.45E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "466500 12 196.69 -3.77E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "467000 10 240.4 -4.71E-02 6.45E+00 3.62E+01 8.00E+03\n",
-      "467500 12 196.69 -1.28E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "468000 10 240.4 -4.15E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "468500 11 216.36 -1.12E-02 6.45E+00 3.68E+01 8.00E+03\n",
-      "469000 10 240.4 -3.16E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "469500 11 216.36 -3.84E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "470000 9 270.45 -1.10E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "470500 13 180.3 -1.02E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "471000 5 540.91 -1.20E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "471500 9 270.45 -1.58E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "472000 7 360.6 -2.14E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "472500 8 309.09 -1.08E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "473000 14 166.43 -4.44E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "473500 8 309.09 -1.56E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "474000 11 216.36 -2.44E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "474500 15 154.54 -5.15E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "475000 10 240.4 -3.49E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "475500 8 309.09 -5.08E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "476000 15 154.54 -1.89E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "476500 14 166.43 -7.80E-02 6.45E+00 3.99E+01 8.00E+03\n",
-      "477000 5 540.91 -2.97E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "477500 9 270.45 -3.83E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "478000 6 432.72 -5.89E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "478500 11 216.36 -4.27E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "479000 9 270.45 -1.72E-02 6.45E+00 3.93E+01 8.00E+03\n",
-      "479500 11 216.36 -1.42E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "480000 12 196.69 -9.43E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "480500 12 196.69 -3.76E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "481000 9 270.45 -9.85E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "481500 9 270.45 -2.56E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "482000 13 180.3 -9.30E-02 6.45E+00 3.83E+01 8.00E+03\n",
-      "482500 11 216.36 -1.61E-01 6.45E+00 3.79E+01 8.00E+03\n",
-      "483000 12 196.69 -8.31E-02 6.45E+00 3.89E+01 8.00E+03\n",
-      "483500 12 196.69 -5.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "484000 11 216.36 -8.29E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "484500 3 1081.81 -5.79E-07 6.45E+00 3.69E+01 8.00E+03\n",
-      "485000 5 540.91 -2.32E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "485500 13 180.3 -1.84E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "486000 15 154.54 -7.44E-02 6.45E+00 4.85E+01 8.00E+03\n",
-      "486500 14 166.43 -2.30E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "487000 7 360.6 -6.98E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "487500 13 180.3 -3.72E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "488000 11 216.36 -2.30E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "488500 8 309.09 -7.39E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "489000 7 360.6 -1.18E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "489500 8 309.09 -4.36E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "490000 14 166.43 -1.11E-01 6.45E+00 3.71E+01 8.00E+03\n",
-      "490500 11 216.36 -6.20E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "491000 17 135.23 -1.61E-02 6.45E+00 3.66E+01 8.00E+03\n",
-      "491500 9 270.45 -1.66E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "492000 7 360.6 -2.40E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "492500 6 432.72 -3.67E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "493000 16 144.24 -2.56E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "493500 6 432.72 -1.53E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "494000 9 270.45 -4.25E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "494500 9 270.45 -1.31E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "495000 10 240.4 -2.35E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "495500 5 540.91 -8.11E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "496000 15 154.54 -3.27E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "496500 12 196.69 1.30E-01 6.45E+00 5.00E+01 8.00E+03\n",
-      "497000 14 166.43 -1.16E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "497500 8 309.09 -1.04E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "498000 10 240.4 -9.15E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "498500 13 180.3 -8.03E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "499000 12 196.69 -5.87E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "499500 17 135.23 -6.50E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "500000 9 270.45 -2.23E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "500500 14 166.43 1.60E-01 6.45E+00 -2.28E+02 8.00E+03\n",
-      "501000 13 180.3 -1.50E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "501500 6 432.72 -1.43E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "502000 10 240.4 -2.65E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "502500 10 240.4 -4.10E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "503000 13 180.3 -1.50E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "503500 11 216.36 -6.61E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "504000 7 360.6 -4.20E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "504500 15 154.54 5.73E-02 6.45E+00 4.66E+01 8.00E+03\n",
-      "505000 9 270.45 -2.48E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "505500 11 216.36 -7.07E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "506000 7 360.6 -5.29E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "506500 10 240.4 -3.02E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "507000 6 432.72 -5.12E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "507500 6 432.72 -1.63E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "508000 10 240.4 -7.46E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "508500 8 309.09 -2.16E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "509000 7 360.6 -9.21E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "509500 5 540.91 -6.26E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "510000 8 309.09 -2.90E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "510500 14 166.43 -3.41E-02 6.45E+00 3.63E+01 8.00E+03\n",
-      "511000 7 360.6 -3.03E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "511500 13 180.3 -4.23E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "512000 8 309.09 -1.62E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "512500 5 540.91 -2.36E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "513000 5 540.91 -1.51E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "513500 13 180.3 -1.45E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "514000 7 360.6 -3.42E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "514500 10 240.4 -2.89E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "515000 13 180.3 -1.39E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "515500 14 166.43 -1.06E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "516000 9 270.45 -1.81E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "516500 12 196.69 -4.96E-02 6.45E+00 3.61E+01 8.00E+03\n",
-      "517000 10 240.4 -3.82E-02 6.45E+00 4.17E+01 8.00E+03\n",
-      "517500 6 432.72 -8.92E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "518000 6 432.72 -7.98E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "518500 11 216.36 -1.16E-01 6.45E+00 4.32E+01 8.00E+03\n",
-      "519000 4 721.21 -1.67E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "519500 9 270.45 -2.10E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "520000 10 240.4 -2.27E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "520500 8 309.09 -2.10E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "521000 6 432.72 -2.20E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "521500 18 127.27 -1.03E-01 6.45E+00 3.65E+01 8.00E+03\n",
-      "522000 13 180.3 -1.08E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "522500 9 270.45 -4.10E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "523000 11 216.36 -1.11E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "523500 14 166.43 -4.94E-02 6.45E+00 3.61E+01 8.00E+03\n",
-      "524000 7 360.6 -3.01E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "524500 12 196.69 -4.62E-02 6.45E+00 4.24E+01 8.00E+03\n",
-      "525000 8 309.09 -2.21E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "525500 9 270.45 -2.14E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "526000 13 180.3 -8.11E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "526500 8 309.09 -1.96E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "527000 11 216.36 -7.58E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "527500 5 540.91 -1.86E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "528000 10 240.4 -8.51E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "528500 9 270.45 -1.55E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "529000 3 1081.81 -3.63E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "529500 9 270.45 7.75E-02 6.45E+00 5.02E+01 8.00E+03\n",
-      "530000 6 432.72 -3.20E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "530500 12 196.69 -5.49E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "531000 7 360.6 -1.22E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "531500 18 127.27 -5.77E-02 6.45E+00 3.60E+01 8.00E+03\n",
-      "532000 7 360.6 -1.69E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "532500 15 154.54 -3.65E-02 6.45E+00 3.63E+01 8.00E+03\n",
-      "533000 10 240.4 -3.97E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "533500 10 240.4 -5.48E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "534000 21 108.18 -8.96E-02 6.45E+00 3.86E+01 8.00E+03\n",
-      "534500 15 154.54 -8.56E-03 6.45E+00 3.73E+01 8.00E+03\n",
-      "535000 8 309.09 -6.00E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "535500 10 240.4 -2.15E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "536000 10 240.4 -1.07E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "536500 12 196.69 -1.17E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "537000 6 432.72 -3.31E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "537500 11 216.36 -1.69E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "538000 14 166.43 -6.71E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "538500 9 270.45 -2.09E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "539000 7 360.6 -7.13E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "539500 17 135.23 -9.05E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "540000 8 309.09 -2.84E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "540500 14 166.43 -5.45E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "541000 9 270.45 -1.25E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "541500 5 540.91 -2.93E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "542000 8 309.09 -4.26E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "542500 7 360.6 -5.83E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "543000 14 166.43 -7.26E-02 6.45E+00 3.59E+01 8.00E+03\n",
-      "543500 14 166.43 -5.11E-03 6.45E+00 3.73E+01 8.00E+03\n",
-      "544000 8 309.09 -4.00E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "544500 9 270.45 -1.47E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "545000 15 154.54 -1.46E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "545500 11 216.36 -4.68E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "546000 9 270.45 -3.04E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "546500 5 540.91 -3.05E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "547000 9 270.45 -5.11E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "547500 11 216.36 -1.85E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "548000 10 240.4 -3.76E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "548500 7 360.6 -4.33E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "549000 9 270.45 -9.40E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "549500 8 309.09 -1.92E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "550000 7 360.6 -3.00E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "550500 8 309.09 -1.10E-02 6.45E+00 3.67E+01 8.00E+03\n",
-      "551000 8 309.09 -5.36E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "551500 8 309.09 -2.44E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "552000 10 240.4 -8.04E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "552500 3 1081.81 -1.22E-06 6.45E+00 3.69E+01 8.00E+03\n",
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-      "553500 7 360.6 -2.10E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "554000 9 270.45 -5.52E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "554500 6 432.72 -8.83E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "555000 11 216.36 -5.36E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "555500 8 309.09 -3.36E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "556000 8 309.09 -1.38E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "556500 6 432.72 -6.87E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "557000 10 240.4 -9.21E-03 6.45E+00 3.67E+01 8.00E+03\n",
-      "557500 8 309.09 -3.17E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "558000 7 360.6 -5.32E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "558500 12 196.69 -3.11E-02 6.45E+00 3.86E+01 8.00E+03\n",
-      "559000 14 166.43 -2.41E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "559500 12 196.69 -7.75E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "560000 11 216.36 -1.21E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "560500 8 309.09 -6.15E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "561000 11 216.36 -8.75E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "561500 13 180.3 -5.01E-02 6.45E+00 4.10E+01 8.00E+03\n",
-      "562000 7 360.6 -5.77E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "562500 11 216.36 -1.02E-01 6.45E+00 3.75E+01 8.00E+03\n",
-      "563000 7 360.6 -5.91E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "563500 13 180.3 -3.56E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "564000 6 432.72 -5.43E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "564500 7 360.6 -1.55E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "565000 10 240.4 -2.21E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "565500 9 270.45 -2.09E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "566000 8 309.09 -1.33E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "566500 5 540.91 -1.20E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "567000 8 309.09 -3.15E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "567500 5 540.91 -4.55E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "568000 12 196.69 -1.55E-03 6.45E+00 3.70E+01 8.00E+03\n",
-      "568500 12 196.69 -3.76E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "569000 16 144.24 -1.83E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "569500 8 309.09 -1.12E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "570000 13 180.3 -6.34E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "570500 15 154.54 -8.80E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "571000 11 216.36 -8.98E-04 6.45E+00 3.69E+01 8.00E+03\n",
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-      "572000 9 270.45 -2.82E-03 6.45E+00 3.68E+01 8.00E+03\n",
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-      "573000 9 270.45 -2.18E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "573500 9 270.45 -5.70E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "574000 7 360.6 -2.47E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "574500 8 309.09 -5.70E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "575000 15 154.54 -3.70E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "575500 13 180.3 -1.38E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "576000 20 113.87 -2.11E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "576500 20 113.87 -7.10E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "577000 6 432.72 -8.02E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "577500 10 240.4 -7.76E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "578000 6 432.72 -1.63E-05 6.45E+00 3.69E+01 8.00E+03\n",
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-      "579000 10 240.4 -3.46E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "579500 13 180.3 -3.80E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "580000 10 240.4 -2.70E-02 6.45E+00 3.71E+01 8.00E+03\n",
-      "580500 7 360.6 -1.08E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "581000 6 432.72 -3.55E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "581500 9 270.45 -2.79E-02 6.45E+00 3.64E+01 8.00E+03\n",
-      "582000 9 270.45 -5.45E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "582500 10 240.4 -4.38E-03 6.45E+00 3.74E+01 8.00E+03\n",
-      "583000 11 216.36 -3.41E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "583500 8 309.09 -1.09E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "584000 10 240.4 -1.56E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "584500 8 309.09 -4.25E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "585000 8 309.09 -1.13E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "585500 8 309.09 -3.27E-03 6.45E+00 3.72E+01 8.00E+03\n",
-      "586000 12 196.69 -2.26E-02 6.45E+00 3.65E+01 8.00E+03\n",
-      "586500 9 270.45 -8.96E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "587000 6 432.72 -2.51E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "587500 12 196.69 -5.40E-03 6.45E+00 3.74E+01 8.00E+03\n",
-      "588000 7 360.6 -6.49E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "588500 8 309.09 -2.38E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "589000 8 309.09 -1.42E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "589500 6 432.72 -3.45E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "590000 8 309.09 -3.96E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "590500 14 166.43 -2.59E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "591000 7 360.6 -7.01E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "591500 11 216.36 -7.04E-02 6.45E+00 3.98E+01 8.00E+03\n",
-      "592000 9 270.45 -1.46E-03 6.45E+00 3.68E+01 8.00E+03\n",
-      "592500 8 309.09 -2.14E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "593000 8 309.09 -1.12E-03 6.45E+00 3.69E+01 8.00E+03\n",
-      "593500 7 360.6 -3.01E-05 6.45E+00 3.69E+01 8.00E+03\n",
-      "594000 4 721.21 -5.70E-06 6.45E+00 3.69E+01 8.00E+03\n",
-      "594500 11 216.36 -1.57E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "595000 8 309.09 -6.82E-04 6.45E+00 3.68E+01 8.00E+03\n",
-      "595500 9 270.45 -4.96E-04 6.45E+00 3.69E+01 8.00E+03\n",
-      "596000 7 360.6 -4.20E-03 6.45E+00 3.68E+01 8.00E+03\n"
-     ]
-    },
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[4], line 14\u001b[0m\n\u001b[1;32m      2\u001b[0m sys\u001b[39m.\u001b[39mpath\u001b[39m.\u001b[39mappend(\u001b[39m\"\u001b[39m\u001b[39m../../molecular-simulation/\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m      3\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mmain\u001b[39;00m \u001b[39mimport\u001b[39;00m MonteCarlo\n\u001b[1;32m      5\u001b[0m MonteCarlo(number_atoms\u001b[39m=\u001b[39;49m\u001b[39m25\u001b[39;49m,\n\u001b[1;32m      6\u001b[0m             Lx\u001b[39m=\u001b[39;49m\u001b[39m20\u001b[39;49m,\n\u001b[1;32m      7\u001b[0m             maximum_steps\u001b[39m=\u001b[39;49m\u001b[39m2000000\u001b[39;49m,\n\u001b[1;32m      8\u001b[0m             dimensions\u001b[39m=\u001b[39;49m \u001b[39m3\u001b[39;49m,\n\u001b[1;32m      9\u001b[0m             desired_temperature\u001b[39m=\u001b[39;49m\u001b[39m300\u001b[39;49m,\n\u001b[1;32m     10\u001b[0m             seed\u001b[39m=\u001b[39;49m\u001b[39m41982\u001b[39;49m,\n\u001b[1;32m     11\u001b[0m             thermo\u001b[39m=\u001b[39;49m\u001b[39m500\u001b[39;49m,\n\u001b[1;32m     12\u001b[0m             dump\u001b[39m=\u001b[39;49m\u001b[39m500\u001b[39;49m,\n\u001b[1;32m     13\u001b[0m             mu\u001b[39m=\u001b[39;49m\u001b[39m-\u001b[39;49m\u001b[39m4\u001b[39;49m,\n\u001b[0;32m---> 14\u001b[0m             )\u001b[39m.\u001b[39;49mrun()\n",
-      "File \u001b[0;32m~/Git/Personal/mdcourse.github.io/benchmark/python_mu2_1.7nm3_300K_GCMC/../../molecular-simulation/main.py:396\u001b[0m, in \u001b[0;36mMonteCarlo.run\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    394\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mmu \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m    395\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mmonte_carlo_insert_delete()\n\u001b[0;32m--> 396\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mwrap_in_box()\n\u001b[1;32m    397\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mupdate_log()\n\u001b[1;32m    398\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mupdate_dump(velocity\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m)\n",
-      "File \u001b[0;32m~/Git/Personal/mdcourse.github.io/benchmark/python_mu2_1.7nm3_300K_GCMC/../../molecular-simulation/main.py:111\u001b[0m, in \u001b[0;36mInitializeSimulation.wrap_in_box\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    109\u001b[0m \u001b[39mfor\u001b[39;00m dim \u001b[39min\u001b[39;00m np\u001b[39m.\u001b[39marange(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdimensions):\n\u001b[1;32m    110\u001b[0m     out_ids \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39matoms_positions[:, dim] \u001b[39m>\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mbox_boundaries[dim][\u001b[39m1\u001b[39m]\n\u001b[0;32m--> 111\u001b[0m     \u001b[39mif\u001b[39;00m np\u001b[39m.\u001b[39;49msum(out_ids) \u001b[39m>\u001b[39m \u001b[39m0\u001b[39m:\n\u001b[1;32m    112\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39matoms_positions[:, dim][out_ids] \u001b[39m-\u001b[39m\u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mdiff(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mbox_boundaries[dim])[\u001b[39m0\u001b[39m]\n\u001b[1;32m    113\u001b[0m     out_ids \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39matoms_positions[:, dim] \u001b[39m<\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mbox_boundaries[dim][\u001b[39m0\u001b[39m]\n",
-      "File \u001b[0;32m<__array_function__ internals>:180\u001b[0m, in \u001b[0;36msum\u001b[0;34m(*args, **kwargs)\u001b[0m\n",
-      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/numpy/core/fromnumeric.py:2183\u001b[0m, in \u001b[0;36m_sum_dispatcher\u001b[0;34m(a, axis, dtype, out, keepdims, initial, where)\u001b[0m\n\u001b[1;32m   2113\u001b[0m \u001b[39m    \u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m   2114\u001b[0m \u001b[39m    Clip (limit) the values in an array.\u001b[39;00m\n\u001b[1;32m   2115\u001b[0m \n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2178\u001b[0m \n\u001b[1;32m   2179\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[1;32m   2180\u001b[0m     \u001b[39mreturn\u001b[39;00m _wrapfunc(a, \u001b[39m'\u001b[39m\u001b[39mclip\u001b[39m\u001b[39m'\u001b[39m, a_min, a_max, out\u001b[39m=\u001b[39mout, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m-> 2183\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_sum_dispatcher\u001b[39m(a, axis\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, dtype\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, out\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, keepdims\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m,\n\u001b[1;32m   2184\u001b[0m                     initial\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, where\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m):\n\u001b[1;32m   2185\u001b[0m     \u001b[39mreturn\u001b[39;00m (a, out)\n\u001b[1;32m   2188\u001b[0m \u001b[39m@array_function_dispatch\u001b[39m(_sum_dispatcher)\n\u001b[1;32m   2189\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39msum\u001b[39m(a, axis\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, dtype\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, out\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, keepdims\u001b[39m=\u001b[39mnp\u001b[39m.\u001b[39m_NoValue,\n\u001b[1;32m   2190\u001b[0m         initial\u001b[39m=\u001b[39mnp\u001b[39m.\u001b[39m_NoValue, where\u001b[39m=\u001b[39mnp\u001b[39m.\u001b[39m_NoValue):\n",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "sys.path.append(\"../../molecular-simulation/\")\n",
-    "from main import MonteCarlo\n",
-    "\n",
-    "MonteCarlo(number_atoms=25,\n",
-    "            Lx=20,\n",
-    "            maximum_steps=2000000,\n",
-    "            dimensions= 3,\n",
-    "            desired_temperature=300,\n",
-    "            seed=41982,\n",
-    "            thermo=500,\n",
-    "            dump=500,\n",
-    "            mu=-4,\n",
-    "            ).run()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.7"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/benchmark/utilities.py b/benchmark/utilities.py
deleted file mode 100644
index fe293d3..0000000
--- a/benchmark/utilities.py
+++ /dev/null
@@ -1,75 +0,0 @@
-
-import matplotlib.transforms as mtransforms
-from matplotlib.ticker import AutoMinorLocator
-from matplotlib import pyplot as plt
-import numpy as np
-
-fontsize = 35
-fontlegende = 35
-font = {'family': 'sans', 'color':  'black', 'weight': 'normal', 'size': fontsize}
-plt.rcParams.update({"text.usetex": True, "font.family": "serif", "font.serif": ["Palatino"]})
-
-def complete_panel(ax, xlabel, ylabel, gray=[1, 1, 1], cancel_x=False, cancel_y=False, font=font, fontsize=fontsize, linewidth=2, tickwidth1=2.5, tickwidth2=2, legend=True, ncol=1, locator_x = 2, locator_y = 2, title=None):
-    
-    if xlabel is not None:
-        ax.set_xlabel(xlabel, fontdict=font)
-        if cancel_x:
-            ax.set_xticklabels([])
-    else:
-        ax.set_xticklabels([])
-
-    if ylabel is not None:
-        ax.set_ylabel(ylabel, fontdict=font)
-        if cancel_y:
-            ax.set_yticklabels([])  
-    else:
-        ax.set_yticklabels([])
-
-    if title is not None:
-        ax.set_title(title, fontdict=font)
-
-    plt.xticks(fontsize=fontsize)
-    plt.yticks(fontsize=fontsize)
-    ax.yaxis.offsetText.set_fontsize(20)
-    ax.minorticks_on()
-
-    ax.tick_params('both', length=10, width=tickwidth1, which='major', direction='in', color=gray)
-    ax.tick_params('both', length=6, width=tickwidth2, which='minor', direction='in', color=gray)
-    ax.xaxis.set_ticks_position('both')
-    ax.yaxis.set_ticks_position('both')
-    ax.xaxis.label.set_color(gray)
-    ax.yaxis.label.set_color(gray)
-
-    ax.spines['left'].set_color(gray)
-    ax.spines['top'].set_color(gray)
-    ax.spines['bottom'].set_color(gray)
-    ax.spines['right'].set_color(gray)
-
-    ax.spines["top"].set_linewidth(linewidth)
-    ax.spines["bottom"].set_linewidth(linewidth)
-    ax.spines["left"].set_linewidth(linewidth)
-    ax.spines["right"].set_linewidth(linewidth)
-
-    ax.tick_params(axis='y', which='both', colors=gray)
-    ax.tick_params(axis='x', which='both', colors=gray)
-
-    minor_locator_x = AutoMinorLocator(locator_x)
-    ax.xaxis.set_minor_locator(minor_locator_x)
-    minor_locator_y = AutoMinorLocator(locator_y)
-    ax.yaxis.set_minor_locator(minor_locator_y)
-
-    if legend:
-        leg = ax.legend(frameon=False, fontsize=fontlegende, 
-                loc='best', handletextpad=0.5, ncol=ncol,
-                handlelength = 0.86, borderpad = 0.3, 
-                labelspacing=0.3)
-        
-        for text in leg.get_texts():
-            text.set_color(gray)
-
-myblue = np.array([20, 100, 255])/255
-myred = np.array([255, 20, 20])/255
-mygray = np.array([50, 50, 50])/255
-myorange = np.array([255, 165, 0])/255
-lightgray = [0.1, 0.1, 0.1]
-darkgray = [0.9, 0.9, 0.9]
\ No newline at end of file
diff --git a/benchmark/velocity_distribution_300K.png b/benchmark/velocity_distribution_300K.png
deleted file mode 100644
index af35c2a..0000000
Binary files a/benchmark/velocity_distribution_300K.png and /dev/null differ
diff --git a/illustration/Equation-of-state/WriteLAMMPSfiles.py b/illustration/Equation-of-state/WriteLAMMPSfiles.py
deleted file mode 100644
index bcfb39c..0000000
--- a/illustration/Equation-of-state/WriteLAMMPSfiles.py
+++ /dev/null
@@ -1,120 +0,0 @@
-import numpy as np
-from scipy import constants as cst
-
-
-def write_topology_file(dictionary,
-                        filename="lammps.data",
-                        velocities=None,
-                        atom_style="atomic"):
-    """Write a LAMMPS data file containing atoms positions and velocities.
-
-    The charge of the atoms is assumed to be 0, and the same
-    molecule id is used for all atoms.
-    """
-    box_boundaries = dictionary.box_boundaries\
-        * dictionary.reference_distance
-    atoms_types = dictionary.atoms_type
-    atoms_positions = dictionary.atoms_positions\
-        * dictionary.reference_distance
-    if velocities is not None:
-        atoms_velocities = dictionary.atoms_velocities\
-            * dictionary.reference_distance/dictionary.reference_time
-    f = open(filename, "w")
-    f.write('# LAMMPS data file\n\n')
-    f.write("%d %s" % (dictionary.total_number_atoms, 'atoms\n'))
-    f.write("%d %s" % (np.max(dictionary.atoms_type), 'atom types\n\n'))
-    for l0, dim in zip(box_boundaries, ["x", "y", "z"]):
-        characters = "%.3f %.3f %s %s"
-        f.write(characters % (l0[0], l0[1], dim+'lo', dim+'hi\n'))
-    f.write('\nAtoms\n\n')
-    cpt = 1
-    for type, xyz in zip(atoms_types, atoms_positions):
-        if atom_style == "atomic":
-            characters = "%d %d %.3f %.3f %.3f %s"
-            v = [cpt, type, xyz[0], xyz[1], xyz[2]]
-            f.write(characters % (v[0], v[1], v[2], v[3], v[4], '\n'))
-        elif atom_style == "molecular":
-            q, mol = 0, cpt
-            characters = "%d %d %d %.3f %.3f %.3f %.3f %s"
-            v = [cpt, mol, type, q, xyz[0], xyz[1], xyz[2]]
-            f.write(characters % (v[0], v[1], v[2], v[3], v[4], v[5], v[6], '\n'))
-        cpt += 1
-    if velocities is not None:
-        f.write('\nVelocities\n\n')
-        cpt = 1
-        for vxyz in atoms_velocities:
-            characters = "%d %.3f %.3f %.3f %s"
-            v = [cpt, vxyz[0], vxyz[1], vxyz[2]]
-            f.write(characters % (cpt, v[0], v[1], v[2], '\n'))
-            cpt += 1
-    f.close()
-
-
-def write_lammps_parameters(dictionary,
-                            filename="PARM.lammps"):
-    """Write a LAMMPS-format parameter file"""
-    f = open(filename, "w")
-    f.write('# LAMMPS parameter file \n\n')
-    for type, mass in zip(np.unique(dictionary.atoms_type),
-                          dictionary.atom_mass):
-        mass *= dictionary.reference_mass
-        f.write("mass "+str(type)+" "+str(mass)+"\n")
-    f.write('\n')
-    for type, epsilon, sigma in zip(np.unique(dictionary.atoms_type),
-                                    dictionary.epsilon,
-                                    dictionary.sigma):
-        epsilon *= dictionary.reference_energy
-        sigma *= dictionary.reference_distance
-        f.write("pair_coeff " + str(type) + " " + str(type) + " " +
-                str(epsilon) + " " + str(sigma) + "\n")
-    f.write('\n')
-    f.close()
-
-
-def write_lammps_variables(self, filename="variable.lammps"):
-    """Write a LAMMPS-format variable file"""
-    f = open(filename, "w")
-    f.write('# LAMMPS variable file \n\n')
-    f.write('variable neighbor equal '
-            + str(self.neighbor) + '\n')
-    f.write('variable thermo equal '
-            + str(self.thermo_period) + '\n')
-    f.write('variable dump equal '
-            + str(self.dumping_period) + '\n')
-    f.write('variable cut_off equal '
-            + str(self.cut_off*self.reference_distance) + '\n')
-    try:
-        f.write('variable displace_mc equal '
-                + str(self.displace_mc*self.reference_distance) + '\n')
-    except:
-        pass
-    try:
-        f.write('variable time_step equal '
-                + str(self.time_step*self.reference_time) + '\n')
-    except:
-        pass
-    # f.write('variable minimization_steps equal '
-    # + str(self.minimization_steps) + '\n')
-    f.write('variable maximum_steps equal '
-            + str(self.maximum_steps) + '\n')
-    kB = cst.Boltzmann*cst.Avogadro/cst.calorie/cst.kilo  # kCal/mol/K
-    f.write('variable temp equal '
-            + str(self.desired_temperature*self.reference_energy/kB) + '\n')
-    try:
-        f.write('variable tau_temp equal '
-                + str(self.tau_temp*self.reference_time) + '\n')
-    except:
-        pass
-    try:
-        if self.tau_press is not None:
-            f.write('variable press equal '
-                    + str(self.desired_pressure * self.reference_pressure) + '\n')
-            f.write('variable tau_press equal '
-                    + str(self.tau_press*self.reference_time) + '\n')
-            f.write('variable pber equal 1')
-        else:
-            f.write('variable pber equal 0')
-    except:
-         pass
-    f.write('\n')
-    f.close()
diff --git a/illustration/Equation-of-state/energy-vs-density-dm.png b/illustration/Equation-of-state/energy-vs-density-dm.png
deleted file mode 100644
index 612200c..0000000
Binary files a/illustration/Equation-of-state/energy-vs-density-dm.png and /dev/null differ
diff --git a/illustration/Equation-of-state/energy-vs-density-pyplot.ipynb b/illustration/Equation-of-state/energy-vs-density-pyplot.ipynb
deleted file mode 100644
index 158f5f8..0000000
--- a/illustration/Equation-of-state/energy-vs-density-pyplot.ipynb
+++ /dev/null
@@ -1,175 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "15134151",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")\n",
-    "\n",
-    "import numpy as np\n",
-    "import sys, os, git\n",
-    "from scipy import constants as cst\n",
-    "from pint import UnitRegistry\n",
-    "ureg = UnitRegistry()\n",
-    "ureg = UnitRegistry(autoconvert_offset_to_baseunit = True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "11014d02",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "current_path = os.getcwd()\n",
-    "git_repo = git.Repo(current_path, search_parent_directories=True)\n",
-    "git_path = git_repo.git.rev_parse(\"--show-toplevel\")\n",
-    "path_in_folder = current_path[len(git_path)+1:]\n",
-    "sys.path.append(git_path + \"/pyplot-perso\")\n",
-    "from plttools import PltTools\n",
-    "path_figures = current_path[len(git_path):] + '/'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Wood1957 = np.loadtxt(\"literature-data/excess-energy.dat\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "d51e3f62",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "kB = cst.Boltzmann*ureg.J/ureg.kelvin # boltzman constant\n",
-    "Na = cst.Avogadro/ureg.mole # avogadro\n",
-    "R = kB*Na # gas constant"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "2927574e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "jump = 10\n",
-    "N_atom = 200\n",
-    "T = (55 * ureg.degC).to(ureg.degK) # 55°C\n",
-    "Epot_vs_tau = []\n",
-    "for folder in [x[0] for x in os.walk(\"./\")]:\n",
-    "    if \"outputs_tau\" in folder:\n",
-    "        Epot = np.mean(np.loadtxt(folder+\"/Epot.dat\")[:,1][jump:]) # kcal/mol\n",
-    "        Epot = (Epot*ureg.kcal/ureg.mol).to(ureg.joule/ureg.mol)\n",
-    "        Enormalised =  Epot / N_atom / R / T # no units\n",
-    "        Epot_vs_tau.append([np.float32(folder.split(\"./outputs_tau\")[1]), Enormalised.magnitude])\n",
-    "Epot_vs_tau = np.array(Epot_vs_tau)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "0c2c7c3c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "jump = 10\n",
-    "N_atom = 200\n",
-    "T = (273.15+55)*ureg.kelvin # 55°C\n",
-    "Epot_vs_tau_lmp = []\n",
-    "for folder in [x[0] for x in os.walk(\"./\")]:\n",
-    "    if \"lammps_tau\" in folder:\n",
-    "        Epot = np.mean(np.loadtxt(folder+\"/Epot.dat\")[:,1][jump:]) # kcal/mol\n",
-    "        Epot = (Epot*ureg.kcal/ureg.mol).to(ureg.joule/ureg.mol)\n",
-    "        Enormalised =  Epot / N_atom / R / T # no units\n",
-    "        Epot_vs_tau_lmp.append([np.float32(folder.split(\"./lammps_tau\")[1]), Enormalised.magnitude])\n",
-    "Epot_vs_tau_lmp = np.array(Epot_vs_tau_lmp)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "19f9a92f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-      "text/plain": [
-       "<Figure size 1800x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1800x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "filename = \"energy-vs-density\"\n",
-    "for dark_mode in [False, True]:\n",
-    "    myplt = PltTools()\n",
-    "    myplt.prepare_figure(fig_size = (18,8), dark_mode = dark_mode,\n",
-    "                        transparency = True, use_serif=True)\n",
-    "    myplt.add_panel()\n",
-    "    myplt.add_plot(x = Wood1957[:,0], y = Wood1957[:,1], type = \"semilogx\",\n",
-    "                   linewidth_data = 3, marker = \"p\", data_color = \"autogray\",\n",
-    "                   markersize = 16, data_label = r'$\\mathrm{Wood1957}$')\n",
-    "    myplt.add_plot(x = Epot_vs_tau_lmp[:,0], y = Epot_vs_tau_lmp[:,1], type = \"semilogx\",\n",
-    "                   linewidth_data = 3, marker = \"s\", data_color = 1,\n",
-    "                   markersize = 16, data_label = r'$\\mathrm{LAMMPS}$')\n",
-    "    myplt.add_plot(x = Epot_vs_tau[:,0], y = Epot_vs_tau[:,1], type = \"semilogx\",\n",
-    "                   linewidth_data = 3, marker = \"o\", data_color = np.array([0, 0.8, 0.8]),\n",
-    "                   markersize = 16, data_label = r'$\\mathrm{MC~move}$')\n",
-    "    myplt.complete_panel(ylabel = r'$E^* / R T$', xlabel = r'$v / v^*$',\n",
-    "                         xpad = 16, legend=True, handlelength_legend=1)\n",
-    "    myplt.set_boundaries(x_boundaries=(0.6, 11), y_ticks=np.arange(-3., 2.1, 1),\n",
-    "                         y_boundaries=(-3, 2))\n",
-    "    myplt.save_figure(filename = filename, saving_path = './')"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3.10.6 64-bit",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.3"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/illustration/Equation-of-state/energy-vs-density.png b/illustration/Equation-of-state/energy-vs-density.png
deleted file mode 100644
index ca891d7..0000000
Binary files a/illustration/Equation-of-state/energy-vs-density.png and /dev/null differ
diff --git a/illustration/Equation-of-state/generate-code.py b/illustration/Equation-of-state/generate-code.py
deleted file mode 100644
index cfa9963..0000000
--- a/illustration/Equation-of-state/generate-code.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import os, git, sys
-import numpy as np
-
-# detect the path to the documentation
-current_path = os.getcwd()
-git_repo = git.Repo(current_path, search_parent_directories=True)
-git_path = git_repo.git.rev_parse("--show-toplevel")
-path_to_docs = git_path + "/mdcourse.github.io/docs/source/chapters/"
-
-# import the python converter
-path_to_converter = git_path + "/mdcourse.github.io/tests/"
-sys.path.append(path_to_converter)
-from utilities import sphinx_to_python
-
-# make sure the documentation was found
-assert os.path.exists(path_to_docs), """Documentation files not found"""
-
-# if necessary, create the "generated-codes/" folder
-if os.path.exists("generated-codes/") is False:
-    os.mkdir("generated-codes/")
-
-# Choose a desired chapter id to build the code from
-# max_chapter_id = 6
-for chapter_id in [1, 2, 3, 4, 5, 6, 7]:
-    RST_EXISTS, created_tests, folder = sphinx_to_python(path_to_docs, chapter_id)
diff --git a/illustration/Equation-of-state/illustration.ipynb b/illustration/Equation-of-state/illustration.ipynb
deleted file mode 100644
index ef7f747..0000000
--- a/illustration/Equation-of-state/illustration.ipynb
+++ /dev/null
@@ -1,164 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")\n",
-    "\n",
-    "from scipy import constants as cst\n",
-    "from pint import UnitRegistry\n",
-    "ureg = UnitRegistry()\n",
-    "ureg = UnitRegistry(autoconvert_offset_to_baseunit = True)\n",
-    "import sys\n",
-    "import multiprocessing\n",
-    "import subprocess\n",
-    "import numpy as np\n",
-    "import shutil\n",
-    "import os\n",
-    "\n",
-    "path_to_code = \"generated-codes/chapter7/\"\n",
-    "sys.path.append(path_to_code)\n",
-    "\n",
-    "from MinimizeEnergy import MinimizeEnergy\n",
-    "from MonteCarlo import MonteCarlo\n",
-    "from WriteLAMMPSfiles import write_topology_file, write_lammps_parameters, write_lammps_variables"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "\"The values of the potential constants for argon have been taken throughout as  \n",
-    "E*/k= 119.76°K, r*=3.822 A, v*=23.79 cm3/mole, as determined by Michels6 from  \n",
-    "second virial coefficient data.\" [1]  \n",
-    "\n",
-    "[1] Wood and Parker. The Journal of Chemical Physics, 27(3):720–733, 1957.  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "kB = cst.Boltzmann*ureg.J/ureg.kelvin # boltzman constant\n",
-    "Na = cst.Avogadro/ureg.mole # avogadro\n",
-    "R = kB*Na # gas constant"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def launch_MC_code(tau):\n",
-    "\n",
-    "    epsilon = (119.76*ureg.kelvin*kB*Na).to(ureg.kcal/ureg.mol) # kcal/mol\n",
-    "    r_star = 3.822*ureg.angstrom # angstrom\n",
-    "    sigma = r_star / 2**(1/6) # angstrom\n",
-    "    N_atom = 200 # no units\n",
-    "    m_argon = 39.948*ureg.gram/ureg.mol\n",
-    "    T = (55 * ureg.degC).to(ureg.degK) # 55°C\n",
-    "    volume_star = r_star**3 * Na * 2**(-0.5)\n",
-    "    cut_off = sigma*2.5\n",
-    "    displace_mc = sigma/5 # angstrom\n",
-    "    volume = N_atom*volume_star*tau/Na\n",
-    "    L = volume**(1/3)\n",
-    "    folder = \"outputs_tau\"+str(tau)+\"/\"\n",
-    "\n",
-    "    em = MinimizeEnergy(\n",
-    "        ureg = ureg,\n",
-    "        maximum_steps=100,\n",
-    "        thermo_period=10,\n",
-    "        dumping_period=10,\n",
-    "        number_atoms=[N_atom],\n",
-    "        epsilon=[epsilon], \n",
-    "        sigma=[sigma],\n",
-    "        atom_mass=[m_argon],\n",
-    "        box_dimensions=[L, L, L],\n",
-    "        cut_off=cut_off,\n",
-    "        data_folder=folder,\n",
-    "        thermo_outputs=\"Epot-MaxF\",\n",
-    "        neighbor=20,\n",
-    "    )\n",
-    "    em.run()\n",
-    "\n",
-    "    minimized_positions = em.atoms_positions*em.ref_length\n",
-    "\n",
-    "    mc = MonteCarlo(\n",
-    "        ureg = ureg,\n",
-    "        maximum_steps=20000,\n",
-    "        dumping_period=1000,\n",
-    "        thermo_period=1000,\n",
-    "        neighbor=50,\n",
-    "        displace_mc = displace_mc,\n",
-    "        desired_temperature = T,\n",
-    "        number_atoms=[N_atom],\n",
-    "        epsilon=[epsilon], \n",
-    "        sigma=[sigma],\n",
-    "        atom_mass=[m_argon],\n",
-    "        box_dimensions=[L, L, L],\n",
-    "        initial_positions = minimized_positions,\n",
-    "        cut_off=cut_off,\n",
-    "        data_folder=folder,\n",
-    "        thermo_outputs=\"Epot-press\",\n",
-    "    )\n",
-    "    mc.run()\n",
-    "\n",
-    "    folder = \"lammps_tau\"+str(tau)+\"/\"\n",
-    "    if os.path.exists(folder) is False:\n",
-    "        os.mkdir(folder)\n",
-    "\n",
-    "    write_topology_file(mc, filename=folder+\"initial.data\")\n",
-    "    write_lammps_parameters(mc, filename=folder+\"PARM.lammps\")\n",
-    "    write_lammps_variables(mc, filename=folder+\"variable.lammps\")\n",
-    "\n",
-    "    mycwd = os.getcwd() # initial path\n",
-    "    os.chdir(folder)\n",
-    "    shutil.copyfile(\"../lammps/input.lmp\", \"input.lmp\")\n",
-    "    subprocess.call([\"/home/simon/Softwares/lammps-2Aug2023/src/lmp_serial\", \"-in\", \"input.lmp\"])\n",
-    "    os.chdir(mycwd)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "if __name__ == \"__main__\":\n",
-    "    tau_values = np.round(np.logspace(-0.126, 0.882, 10),2)\n",
-    "    pool = multiprocessing.Pool()\n",
-    "    squared_numbers = pool.map(launch_MC_code, tau_values)\n",
-    "    pool.close()\n",
-    "    pool.join()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/illustration/Equation-of-state/lammps/input.lmp b/illustration/Equation-of-state/lammps/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau0.75/Epot.dat b/illustration/Equation-of-state/lammps_tau0.75/Epot.dat
deleted file mode 100644
index f1a58a3..0000000
--- a/illustration/Equation-of-state/lammps_tau0.75/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 125.058
-1000 127.665
-2000 120.939
-3000 121.416
-4000 121.795
-5000 122.378
-6000 113.006
-7000 104.662
-8000 116.907
-9000 119.619
-10000 122.086
-11000 107.38
-12000 113.401
-13000 128.844
-14000 119.339
-15000 122.48
-16000 114.038
-17000 111.727
-18000 83.1278
-19000 97.9686
-20000 92.9485
diff --git a/illustration/Equation-of-state/lammps_tau0.75/PARM.lammps b/illustration/Equation-of-state/lammps_tau0.75/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau0.75/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau0.75/initial.data b/illustration/Equation-of-state/lammps_tau0.75/initial.data
deleted file mode 100644
index b0ddcae..0000000
--- a/illustration/Equation-of-state/lammps_tau0.75/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--9.046 9.046 xlo xhi
--9.046 9.046 ylo yhi
--9.046 9.046 zlo zhi
-
-Atoms
-
-1 1 -7.051 -6.331 5.685 
-2 1 6.983 8.017 3.834 
-3 1 5.378 -6.366 -1.627 
-4 1 -3.809 3.286 5.973 
-5 1 8.750 -4.449 6.674 
-6 1 -6.110 -1.154 -0.560 
-7 1 -2.234 0.858 -6.843 
-8 1 -0.492 1.179 4.820 
-9 1 -8.862 2.100 3.613 
-10 1 -2.813 3.008 2.616 
-11 1 6.849 -2.005 7.230 
-12 1 4.971 -8.977 6.184 
-13 1 3.037 -8.679 -2.771 
-14 1 -0.057 -4.222 -5.100 
-15 1 5.693 -5.465 6.310 
-16 1 -4.434 8.038 -0.863 
-17 1 2.246 -0.587 -0.529 
-18 1 7.296 7.331 -7.314 
-19 1 -1.293 5.834 0.805 
-20 1 -8.887 -4.494 -8.374 
-21 1 -6.810 -2.959 4.760 
-22 1 -0.788 3.767 6.358 
-23 1 9.019 -1.294 -4.940 
-24 1 -7.640 -8.482 -0.585 
-25 1 8.740 -4.496 -4.495 
-26 1 -5.186 6.299 5.252 
-27 1 5.962 -2.690 4.111 
-28 1 -1.288 -8.901 -0.256 
-29 1 3.971 7.289 3.190 
-30 1 8.087 -7.294 -2.931 
-31 1 7.831 -6.711 0.680 
-32 1 7.684 4.172 7.312 
-33 1 -9.008 4.620 -7.652 
-34 1 5.884 3.837 -2.856 
-35 1 -7.568 2.471 -3.114 
-36 1 -8.413 -7.956 3.150 
-37 1 7.100 2.442 -8.341 
-38 1 3.252 -7.781 8.773 
-39 1 -7.458 2.134 -6.435 
-40 1 2.905 0.250 -4.852 
-41 1 -6.656 -2.571 -3.581 
-42 1 -0.029 -7.415 8.075 
-43 1 1.832 0.209 6.992 
-44 1 -0.923 -7.563 -3.920 
-45 1 -6.032 6.643 -6.323 
-46 1 8.389 -0.096 -7.752 
-47 1 2.833 -5.895 -4.345 
-48 1 -8.511 4.974 4.903 
-49 1 -3.451 -6.601 6.505 
-50 1 5.309 -0.503 -8.366 
-51 1 2.878 6.354 -2.687 
-52 1 7.986 1.932 -5.083 
-53 1 2.650 -2.709 -3.401 
-54 1 -8.328 7.647 -8.963 
-55 1 -2.913 -8.336 -8.910 
-56 1 1.860 8.900 5.592 
-57 1 -0.140 -0.692 -5.317 
-58 1 -0.136 0.159 1.563 
-59 1 1.921 6.160 0.157 
-60 1 -4.694 -5.726 3.656 
-61 1 -5.443 3.603 0.337 
-62 1 -6.738 8.112 -3.338 
-63 1 -1.005 -4.947 -2.207 
-64 1 7.573 -6.901 -6.321 
-65 1 2.184 -5.734 -1.271 
-66 1 -2.435 8.442 6.025 
-67 1 3.770 2.772 -0.619 
-68 1 5.345 5.526 0.070 
-69 1 6.942 7.291 7.296 
-70 1 -0.756 -1.674 -8.255 
-71 1 -1.524 2.195 -0.194 
-72 1 6.937 -2.418 -2.398 
-73 1 -6.616 -4.364 -6.041 
-74 1 -8.864 -4.692 -1.403 
-75 1 6.112 2.013 2.478 
-76 1 1.631 8.380 -5.431 
-77 1 8.175 8.272 -4.536 
-78 1 0.982 1.139 -2.685 
-79 1 1.836 3.971 8.937 
-80 1 -3.254 -2.261 -5.418 
-81 1 6.034 8.456 -1.409 
-82 1 5.125 5.199 8.856 
-83 1 2.460 5.327 -6.122 
-84 1 2.752 7.132 8.466 
-85 1 0.411 2.611 -6.198 
-86 1 -7.768 -2.758 1.473 
-87 1 0.613 3.644 2.540 
-88 1 -5.267 -8.760 4.520 
-89 1 1.781 -3.456 1.029 
-90 1 4.538 -6.242 -6.857 
-91 1 -3.831 0.349 4.608 
-92 1 2.956 3.085 -3.693 
-93 1 2.822 -7.387 3.244 
-94 1 0.187 -6.691 1.301 
-95 1 -0.624 1.626 8.744 
-96 1 -0.286 5.737 -5.069 
-97 1 8.855 4.539 1.166 
-98 1 -4.195 -8.177 -5.716 
-99 1 -3.832 -7.642 -2.731 
-100 1 4.945 0.391 4.890 
-101 1 5.846 -0.321 -5.298 
-102 1 7.588 1.167 6.307 
-103 1 5.464 -8.111 -4.361 
-104 1 0.844 -7.131 -7.019 
-105 1 -7.306 -8.547 -6.538 
-106 1 -1.438 -4.812 8.254 
-107 1 1.882 -1.516 4.071 
-108 1 -7.700 1.641 0.070 
-109 1 -1.363 -3.080 0.612 
-110 1 2.187 0.062 -7.930 
-111 1 -3.036 6.999 -6.793 
-112 1 -5.209 -1.216 7.377 
-113 1 -8.258 -1.397 7.553 
-114 1 5.761 -4.582 9.024 
-115 1 -5.694 5.102 -3.433 
-116 1 8.950 -4.417 3.670 
-117 1 -5.318 -8.084 1.371 
-118 1 -7.094 6.272 -0.506 
-119 1 -4.708 1.239 9.005 
-120 1 -0.244 -7.272 4.720 
-121 1 2.048 2.883 5.372 
-122 1 6.978 -3.704 0.911 
-123 1 -4.032 -4.888 -4.225 
-124 1 -4.564 1.399 -1.635 
-125 1 -1.696 -4.886 3.335 
-126 1 -9.013 -0.340 -2.051 
-127 1 -6.800 -0.089 2.924 
-128 1 4.339 -5.388 1.470 
-129 1 -4.774 -2.954 2.033 
-130 1 -0.266 6.671 7.151 
-131 1 -5.309 -6.409 -8.256 
-132 1 -6.207 -4.227 7.864 
-133 1 -8.004 8.242 5.919 
-134 1 7.942 5.889 -1.661 
-135 1 6.596 5.054 3.464 
-136 1 2.038 -5.824 6.532 
-137 1 -5.358 0.244 -4.955 
-138 1 -8.199 -7.288 8.721 
-139 1 2.724 1.208 2.696 
-140 1 -5.559 8.979 7.993 
-141 1 -6.740 -6.704 -3.508 
-142 1 4.253 8.601 -7.007 
-143 1 4.449 -3.097 -1.000 
-144 1 -1.635 6.125 4.010 
-145 1 -2.265 0.904 -3.368 
-146 1 3.742 -2.654 -6.695 
-147 1 2.614 -4.467 3.698 
-148 1 -3.020 3.752 -4.452 
-149 1 0.062 7.707 -2.395 
-150 1 0.696 8.223 2.265 
-151 1 -2.386 -8.387 2.754 
-152 1 1.863 -4.252 -8.687 
-153 1 6.494 -6.386 3.464 
-154 1 -1.527 -1.728 4.037 
-155 1 3.662 -2.775 6.839 
-156 1 5.527 -8.437 1.499 
-157 1 -2.023 -0.573 7.067 
-158 1 0.269 4.439 -1.814 
-159 1 5.459 -4.547 -4.248 
-160 1 -6.803 -1.560 -7.664 
-161 1 7.304 2.425 -0.487 
-162 1 8.496 -0.801 4.065 
-163 1 -7.500 7.056 2.703 
-164 1 -6.847 4.999 7.660 
-165 1 3.653 4.237 2.625 
-166 1 -7.042 -5.594 1.285 
-167 1 -3.455 -3.348 5.649 
-168 1 -2.097 -5.571 -6.761 
-169 1 -0.334 8.033 -8.176 
-170 1 5.414 7.136 -4.263 
-171 1 4.494 2.001 7.982 
-172 1 8.099 -0.087 1.051 
-173 1 1.494 5.835 4.710 
-174 1 -3.296 -2.015 -2.038 
-175 1 4.579 5.504 5.784 
-176 1 2.744 -8.975 0.379 
-177 1 8.157 -7.442 5.960 
-178 1 -2.828 7.231 -3.628 
-179 1 -3.601 -0.072 1.165 
-180 1 -1.013 4.821 -8.389 
-181 1 -8.653 5.083 -4.472 
-182 1 6.285 4.704 -6.227 
-183 1 5.130 0.207 -2.239 
-184 1 4.319 2.440 -6.893 
-185 1 8.136 7.950 0.983 
-186 1 -0.169 -1.823 -2.334 
-187 1 -5.313 -4.565 -1.352 
-188 1 -3.247 4.868 -1.377 
-189 1 -6.010 3.868 3.307 
-190 1 -3.522 6.458 8.112 
-191 1 -4.162 6.641 2.205 
-192 1 7.097 -2.881 -6.738 
-193 1 0.160 -2.918 6.530 
-194 1 -4.234 4.077 -7.381 
-195 1 -7.943 1.809 8.386 
-196 1 -6.597 1.590 5.511 
-197 1 6.370 -7.809 8.948 
-198 1 4.764 -1.035 1.303 
-199 1 -3.654 -3.169 -8.454 
-200 1 -2.924 -6.049 0.554 
diff --git a/illustration/Equation-of-state/lammps_tau0.75/input.lmp b/illustration/Equation-of-state/lammps_tau0.75/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau0.75/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau0.75/pressure.dat b/illustration/Equation-of-state/lammps_tau0.75/pressure.dat
deleted file mode 100644
index fc5b1ec..0000000
--- a/illustration/Equation-of-state/lammps_tau0.75/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 37721
-1000 37826.4
-2000 37456.2
-3000 37437
-4000 37474.2
-5000 37490.6
-6000 37022.2
-7000 36565
-8000 37207.8
-9000 37299.2
-10000 37432.1
-11000 36662.4
-12000 37005
-13000 37885.3
-14000 37392.8
-15000 37539.1
-16000 37095.7
-17000 36960.9
-18000 35476.8
-19000 36298.3
-20000 35995.7
diff --git a/illustration/Equation-of-state/lammps_tau0.75/variable.lammps b/illustration/Equation-of-state/lammps_tau0.75/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau0.75/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/lammps_tau0.97/Epot.dat b/illustration/Equation-of-state/lammps_tau0.97/Epot.dat
deleted file mode 100644
index 2bd89a7..0000000
--- a/illustration/Equation-of-state/lammps_tau0.97/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 -165.009
-1000 -162.92
-2000 -180.047
-3000 -172.19
-4000 -168.216
-5000 -180.395
-6000 -171.69
-7000 -174.01
-8000 -174.34
-9000 -187.04
-10000 -173.151
-11000 -163.135
-12000 -171.456
-13000 -168.551
-14000 -147.388
-15000 -163.365
-16000 -161.373
-17000 -166.004
-18000 -159.463
-19000 -158.594
-20000 -164.473
diff --git a/illustration/Equation-of-state/lammps_tau0.97/PARM.lammps b/illustration/Equation-of-state/lammps_tau0.97/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau0.97/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau0.97/initial.data b/illustration/Equation-of-state/lammps_tau0.97/initial.data
deleted file mode 100644
index b62818e..0000000
--- a/illustration/Equation-of-state/lammps_tau0.97/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--9.856 9.856 xlo xhi
--9.856 9.856 ylo yhi
--9.856 9.856 zlo zhi
-
-Atoms
-
-1 1 -8.199 -7.018 5.225 
-2 1 7.122 8.402 4.388 
-3 1 5.165 -7.123 -0.863 
-4 1 -5.001 3.779 7.364 
-5 1 -9.684 -5.710 7.552 
-6 1 -6.355 -1.288 0.315 
-7 1 -2.024 0.561 -7.001 
-8 1 -1.221 0.392 5.765 
-9 1 8.879 2.955 4.496 
-10 1 -3.216 3.901 3.555 
-11 1 8.181 -3.115 7.883 
-12 1 4.920 -9.687 6.784 
-13 1 3.851 -9.246 -3.454 
-14 1 -1.188 -4.884 -4.352 
-15 1 6.186 -6.263 6.380 
-16 1 -3.931 7.555 -0.633 
-17 1 2.747 -0.978 -0.390 
-18 1 8.156 9.339 -8.240 
-19 1 -1.604 6.027 1.674 
-20 1 -8.321 -5.493 -8.131 
-21 1 -8.840 -2.366 6.348 
-22 1 -0.987 3.501 7.041 
-23 1 -9.637 -0.648 -5.555 
-24 1 -8.338 -9.258 -1.473 
-25 1 8.073 -2.872 -3.844 
-26 1 -5.505 7.618 6.091 
-27 1 6.436 -3.071 4.364 
-28 1 -0.876 8.996 -0.726 
-29 1 3.618 7.949 4.139 
-30 1 9.706 -8.750 -4.557 
-31 1 8.457 -7.578 0.689 
-32 1 8.168 4.568 8.037 
-33 1 9.288 5.419 -8.673 
-34 1 6.227 3.748 -2.296 
-35 1 -8.144 2.096 -4.109 
-36 1 -8.957 -9.288 2.858 
-37 1 7.186 2.392 -9.259 
-38 1 1.169 -9.586 -8.298 
-39 1 -8.203 2.374 -7.434 
-40 1 3.234 -0.205 -3.788 
-41 1 -6.984 -3.860 -1.890 
-42 1 -0.160 -7.975 8.710 
-43 1 1.504 0.516 8.218 
-44 1 -1.895 -8.895 -3.541 
-45 1 -6.170 5.768 -5.971 
-46 1 9.162 -0.289 -9.055 
-47 1 1.730 -7.229 -4.860 
-48 1 -9.334 5.556 5.986 
-49 1 -3.145 -7.034 5.309 
-50 1 5.829 -1.164 9.588 
-51 1 2.312 4.356 -3.456 
-52 1 7.286 1.600 -5.051 
-53 1 2.342 -3.966 -4.553 
-54 1 -8.083 8.291 -7.384 
-55 1 -2.714 -9.468 -9.534 
-56 1 1.485 9.476 5.984 
-57 1 -1.364 -2.659 -7.638 
-58 1 -0.137 0.323 1.179 
-59 1 1.701 7.265 0.559 
-60 1 -5.042 -6.630 2.747 
-61 1 -5.818 4.130 0.276 
-62 1 -7.411 8.043 -3.759 
-63 1 -1.895 -6.366 -1.708 
-64 1 8.697 -6.998 -7.008 
-65 1 1.511 -6.771 -1.723 
-66 1 -2.410 9.721 6.857 
-67 1 3.961 2.294 -0.349 
-68 1 5.105 5.919 -0.146 
-69 1 7.766 7.914 8.498 
-70 1 -2.151 -1.930 8.575 
-71 1 -2.384 2.385 0.566 
-72 1 7.174 -2.978 -0.183 
-73 1 -8.529 -4.085 -4.767 
-74 1 9.702 -5.588 -1.462 
-75 1 5.529 1.985 3.575 
-76 1 1.323 8.694 -5.454 
-77 1 7.841 7.688 -5.228 
-78 1 0.715 1.218 -2.066 
-79 1 1.834 4.300 8.652 
-80 1 -3.598 -2.354 -5.571 
-81 1 6.858 9.209 -1.561 
-82 1 4.994 5.717 -9.107 
-83 1 1.635 5.327 -7.257 
-84 1 2.817 7.771 9.316 
-85 1 0.232 2.146 -5.176 
-86 1 -8.991 -3.189 1.168 
-87 1 -0.039 2.779 3.517 
-88 1 -5.511 -9.414 4.579 
-89 1 0.917 -3.438 3.215 
-90 1 3.222 -6.864 -8.113 
-91 1 -5.024 0.947 2.636 
-92 1 3.552 1.980 -5.948 
-93 1 3.108 -8.012 3.212 
-94 1 0.332 -7.224 1.495 
-95 1 0.557 1.561 -8.424 
-96 1 -1.263 5.581 -6.004 
-97 1 -9.334 4.858 1.285 
-98 1 -4.085 -9.119 -6.414 
-99 1 -5.093 -9.663 -2.909 
-100 1 5.990 -0.384 5.993 
-101 1 6.023 -0.377 -7.105 
-102 1 9.109 1.081 7.161 
-103 1 6.324 -9.302 -5.186 
-104 1 0.211 -5.335 -9.065 
-105 1 -7.155 -8.472 -7.010 
-106 1 -2.627 -5.876 8.340 
-107 1 2.763 -1.942 6.178 
-108 1 -9.414 2.363 -1.113 
-109 1 0.051 -3.520 -0.275 
-110 1 2.515 -1.243 -6.923 
-111 1 -3.926 7.469 -7.495 
-112 1 -4.906 -0.545 6.709 
-113 1 -8.529 -2.789 9.674 
-114 1 7.146 -5.036 -9.293 
-115 1 -7.548 4.954 -2.689 
-116 1 9.373 -4.180 4.123 
-117 1 -6.093 -9.755 1.264 
-118 1 -7.623 7.322 -0.356 
-119 1 -6.410 0.483 9.557 
-120 1 -0.038 -7.296 5.146 
-121 1 2.413 2.548 5.738 
-122 1 5.970 -5.839 1.887 
-123 1 -5.348 -5.021 -6.149 
-124 1 -5.894 1.620 -1.739 
-125 1 -1.983 -5.218 2.865 
-126 1 -9.257 -1.195 -2.069 
-127 1 -8.515 0.443 1.974 
-128 1 3.424 -4.429 0.728 
-129 1 -6.437 -2.137 3.521 
-130 1 0.045 6.745 7.424 
-131 1 -5.255 -7.022 -9.247 
-132 1 -6.318 -5.670 7.817 
-133 1 -9.380 9.300 5.982 
-134 1 8.698 6.448 -2.093 
-135 1 6.438 5.530 3.615 
-136 1 2.418 -6.562 7.511 
-137 1 -6.154 -1.196 -3.932 
-138 1 -8.584 -8.116 9.497 
-139 1 2.639 0.151 3.375 
-140 1 -5.518 -9.770 8.542 
-141 1 -6.898 -7.221 -3.774 
-142 1 4.085 9.044 -7.175 
-143 1 4.736 -3.707 -2.828 
-144 1 -1.830 7.107 4.880 
-145 1 -2.655 1.037 -3.345 
-146 1 4.116 -3.829 -7.949 
-147 1 3.476 -4.908 4.412 
-148 1 -5.184 2.529 -5.037 
-149 1 -0.772 6.953 -3.209 
-150 1 0.316 9.472 2.703 
-151 1 -3.294 -8.772 1.365 
-152 1 1.665 -2.485 9.502 
-153 1 7.801 -7.935 4.057 
-154 1 -2.170 -1.593 3.185 
-155 1 4.454 -3.915 8.084 
-156 1 6.259 -9.718 1.906 
-157 1 -2.687 1.373 9.124 
-158 1 0.360 4.471 0.170 
-159 1 6.185 -5.642 -5.315 
-160 1 -7.021 -1.998 -7.215 
-161 1 7.367 3.475 1.378 
-162 1 9.120 -0.320 4.278 
-163 1 -7.898 7.190 3.344 
-164 1 -8.272 7.707 8.795 
-165 1 3.356 4.214 2.432 
-166 1 -8.009 -6.342 1.055 
-167 1 -3.302 -3.486 5.654 
-168 1 -1.271 -7.023 -7.096 
-169 1 -0.639 7.340 -8.735 
-170 1 4.806 7.284 -4.024 
-171 1 5.590 2.412 7.728 
-172 1 8.062 0.219 0.815 
-173 1 1.285 5.459 4.701 
-174 1 -3.940 -3.748 -2.769 
-175 1 5.068 6.236 6.523 
-176 1 3.499 9.701 0.046 
-177 1 8.322 -8.484 7.457 
-178 1 -3.745 7.070 -4.131 
-179 1 -3.108 -0.875 -0.255 
-180 1 -0.977 4.344 -9.647 
-181 1 9.735 4.956 -5.197 
-182 1 6.058 4.448 -6.056 
-183 1 6.032 0.176 -1.816 
-184 1 3.871 2.070 -9.420 
-185 1 8.710 8.233 1.108 
-186 1 -0.186 -1.633 -3.689 
-187 1 -5.418 -6.992 -0.652 
-188 1 -3.334 4.559 -1.896 
-189 1 -6.433 4.353 3.716 
-190 1 -3.213 6.825 8.375 
-191 1 -4.434 7.124 2.568 
-192 1 8.832 -3.040 -6.980 
-193 1 -0.183 -4.102 6.404 
-194 1 -4.075 3.023 -7.970 
-195 1 -8.582 3.024 8.466 
-196 1 -7.377 1.691 5.581 
-197 1 5.727 -8.083 -9.303 
-198 1 5.017 -1.737 1.867 
-199 1 -4.083 -3.707 -9.311 
-200 1 -4.416 -3.922 0.895 
diff --git a/illustration/Equation-of-state/lammps_tau0.97/input.lmp b/illustration/Equation-of-state/lammps_tau0.97/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau0.97/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau0.97/pressure.dat b/illustration/Equation-of-state/lammps_tau0.97/pressure.dat
deleted file mode 100644
index 24aae6a..0000000
--- a/illustration/Equation-of-state/lammps_tau0.97/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 10111.9
-1000 10207
-2000 9428.63
-3000 9829.14
-4000 9893.71
-5000 9385.06
-6000 9776.47
-7000 9669.08
-8000 9627.31
-9000 9104.53
-10000 9788.04
-11000 10108.8
-12000 9746.14
-13000 9913.63
-14000 10861.5
-15000 10137.9
-16000 10265.6
-17000 10037.3
-18000 10314.1
-19000 10384.2
-20000 10177.2
diff --git a/illustration/Equation-of-state/lammps_tau0.97/variable.lammps b/illustration/Equation-of-state/lammps_tau0.97/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau0.97/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/lammps_tau1.25/Epot.dat b/illustration/Equation-of-state/lammps_tau1.25/Epot.dat
deleted file mode 100644
index 93db43a..0000000
--- a/illustration/Equation-of-state/lammps_tau1.25/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 -186.977
-1000 -188.969
-2000 -180.055
-3000 -183.207
-4000 -192.787
-5000 -192.244
-6000 -182.022
-7000 -176.65
-8000 -186.813
-9000 -184.863
-10000 -188.925
-11000 -175.375
-12000 -182.996
-13000 -180.898
-14000 -182.632
-15000 -177.325
-16000 -194.156
-17000 -187.223
-18000 -191.29
-19000 -173.813
-20000 -187.969
diff --git a/illustration/Equation-of-state/lammps_tau1.25/PARM.lammps b/illustration/Equation-of-state/lammps_tau1.25/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau1.25/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau1.25/initial.data b/illustration/Equation-of-state/lammps_tau1.25/initial.data
deleted file mode 100644
index 378bc02..0000000
--- a/illustration/Equation-of-state/lammps_tau1.25/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--10.725 10.725 xlo xhi
--10.725 10.725 ylo yhi
--10.725 10.725 zlo zhi
-
-Atoms
-
-1 1 -8.862 -7.256 6.529 
-2 1 7.199 8.439 5.659 
-3 1 5.026 -8.098 -3.227 
-4 1 -5.742 3.542 7.689 
-5 1 9.643 -6.274 7.698 
-6 1 -6.662 -1.442 -0.439 
-7 1 -0.035 -0.873 -7.697 
-8 1 -1.047 0.856 6.789 
-9 1 -10.404 3.355 3.405 
-10 1 -2.511 3.496 5.116 
-11 1 10.046 -2.555 8.638 
-12 1 5.324 -10.470 7.514 
-13 1 3.138 9.993 -3.788 
-14 1 -2.421 -4.000 -5.322 
-15 1 5.574 -7.155 8.846 
-16 1 -5.730 8.205 -0.767 
-17 1 1.899 -0.927 1.079 
-18 1 7.961 8.434 -8.426 
-19 1 -1.047 7.874 0.941 
-20 1 10.706 -6.906 -8.240 
-21 1 -9.141 -3.724 6.195 
-22 1 -2.206 4.168 8.944 
-23 1 10.321 -0.817 -5.122 
-24 1 -8.846 -9.242 -0.430 
-25 1 -10.573 -4.237 -4.300 
-26 1 -4.441 9.716 6.632 
-27 1 6.727 -3.402 5.086 
-28 1 0.603 10.286 -0.525 
-29 1 3.800 8.355 4.829 
-30 1 -9.588 -8.472 -5.611 
-31 1 8.707 -8.907 -0.292 
-32 1 7.430 6.326 8.645 
-33 1 10.576 5.763 -7.625 
-34 1 7.615 5.960 -3.224 
-35 1 -8.239 4.105 -4.764 
-36 1 -10.181 -10.148 3.276 
-37 1 9.331 2.295 -8.102 
-38 1 2.727 -10.277 10.708 
-39 1 -8.521 2.807 -7.847 
-40 1 3.815 -0.441 -5.315 
-41 1 -7.645 -3.803 -3.260 
-42 1 -0.625 -7.928 10.286 
-43 1 1.634 -0.351 8.806 
-44 1 -1.116 -8.973 -2.620 
-45 1 -7.221 6.483 -7.476 
-46 1 8.673 0.517 10.611 
-47 1 2.232 -7.459 -5.545 
-48 1 -10.282 6.477 7.135 
-49 1 -3.476 -9.121 4.978 
-50 1 5.564 -0.544 10.242 
-51 1 3.604 6.125 -3.456 
-52 1 7.036 1.211 -4.602 
-53 1 1.580 -3.647 -5.562 
-54 1 -8.225 9.570 -9.820 
-55 1 -4.453 -8.450 -9.876 
-56 1 2.158 9.669 7.312 
-57 1 -2.469 -4.294 -9.312 
-58 1 -0.118 1.404 3.661 
-59 1 2.420 6.706 0.227 
-60 1 -5.294 -6.242 5.065 
-61 1 -7.352 5.382 1.226 
-62 1 -9.470 8.177 -4.896 
-63 1 -0.629 -5.830 -2.955 
-64 1 -10.707 -10.634 -7.950 
-65 1 2.967 -7.885 -0.321 
-66 1 -1.491 10.522 7.837 
-67 1 3.708 2.825 0.083 
-68 1 7.323 6.523 -0.162 
-69 1 10.503 7.590 10.626 
-70 1 -2.744 -2.195 9.523 
-71 1 -2.936 2.631 -2.187 
-72 1 7.283 -3.343 -0.807 
-73 1 -8.201 -5.494 -5.996 
-74 1 -9.864 -6.146 -1.230 
-75 1 6.509 2.503 3.216 
-76 1 0.341 10.161 -6.246 
-77 1 8.721 9.374 -5.340 
-78 1 -0.043 1.118 -0.926 
-79 1 3.165 5.521 10.723 
-80 1 -5.836 -2.276 -5.480 
-81 1 6.657 9.531 -2.442 
-82 1 5.021 8.535 10.246 
-83 1 2.387 4.589 -7.298 
-84 1 2.322 8.060 -8.847 
-85 1 0.702 1.710 -5.580 
-86 1 -8.466 -3.773 2.297 
-87 1 -1.960 4.495 1.679 
-88 1 -6.933 -10.041 4.813 
-89 1 1.300 -4.289 3.430 
-90 1 4.423 -7.759 -9.049 
-91 1 -4.668 0.607 5.017 
-92 1 3.615 2.435 -3.920 
-93 1 3.584 -8.630 3.636 
-94 1 0.454 -8.192 2.352 
-95 1 -0.744 2.373 -9.766 
-96 1 -1.169 6.529 -6.142 
-97 1 10.464 5.418 0.240 
-98 1 -3.801 -8.076 -4.679 
-99 1 -3.117 10.009 -1.708 
-100 1 6.889 -0.305 5.360 
-101 1 6.715 -0.442 -8.136 
-102 1 8.925 2.260 5.806 
-103 1 6.966 -10.026 -6.234 
-104 1 1.240 -5.805 -9.011 
-105 1 -6.270 -10.669 -7.140 
-106 1 -2.482 -5.989 8.187 
-107 1 3.645 -1.471 6.620 
-108 1 -10.100 1.481 0.123 
-109 1 -1.536 -4.079 0.273 
-110 1 3.192 0.288 -8.661 
-111 1 -4.109 7.591 -7.610 
-112 1 -6.815 -1.153 7.942 
-113 1 -9.469 -1.300 -8.610 
-114 1 6.812 -4.495 -10.207 
-115 1 -5.882 8.120 -4.311 
-116 1 9.900 -4.783 4.361 
-117 1 -5.510 -9.924 1.095 
-118 1 -8.493 9.008 0.861 
-119 1 -8.058 0.849 10.545 
-120 1 -0.182 -8.326 5.558 
-121 1 1.170 3.072 8.051 
-122 1 8.986 -6.167 1.149 
-123 1 -5.296 -5.773 -7.696 
-124 1 -6.215 2.713 -0.842 
-125 1 -2.619 -5.462 3.504 
-126 1 10.683 -1.861 -1.692 
-127 1 -7.457 0.155 2.952 
-128 1 4.959 -5.478 2.238 
-129 1 -5.358 -3.288 2.389 
-130 1 0.783 6.368 7.832 
-131 1 -7.525 -7.475 -9.618 
-132 1 -9.199 -5.132 9.670 
-133 1 -10.691 9.668 6.222 
-134 1 9.759 8.891 -1.837 
-135 1 8.410 5.477 4.256 
-136 1 1.903 -7.898 8.003 
-137 1 -7.700 0.248 -3.445 
-138 1 -10.679 -8.280 10.513 
-139 1 3.649 1.693 4.269 
-140 1 -6.441 10.492 8.990 
-141 1 -7.003 -10.551 -2.681 
-142 1 3.710 10.677 -7.252 
-143 1 3.997 -4.310 -2.735 
-144 1 -1.548 7.619 5.726 
-145 1 -3.016 -0.099 -4.520 
-146 1 4.933 -3.986 -7.054 
-147 1 3.580 -5.022 5.513 
-148 1 -5.341 1.996 -5.231 
-149 1 -1.241 8.300 -3.675 
-150 1 1.031 9.593 3.662 
-151 1 -2.483 -10.686 2.372 
-152 1 3.062 -3.027 -10.695 
-153 1 8.143 -7.882 5.074 
-154 1 -1.717 -1.883 3.822 
-155 1 5.829 -3.525 8.386 
-156 1 7.524 -10.536 3.262 
-157 1 -3.854 0.966 9.837 
-158 1 0.218 4.715 -1.009 
-159 1 7.349 -5.294 -4.965 
-160 1 -5.789 -2.451 -9.840 
-161 1 7.647 2.440 -0.929 
-162 1 -10.297 -0.475 4.931 
-163 1 -8.545 7.626 4.169 
-164 1 -7.498 6.457 8.621 
-165 1 5.069 5.257 1.918 
-166 1 -8.252 -7.339 2.206 
-167 1 -4.372 -2.846 5.760 
-168 1 -0.851 -7.819 -7.656 
-169 1 -1.538 9.073 -10.398 
-170 1 5.719 8.066 -5.804 
-171 1 5.957 2.233 7.829 
-172 1 8.286 0.129 1.914 
-173 1 1.181 4.513 3.919 
-174 1 -4.453 -3.666 -2.354 
-175 1 4.650 5.216 5.787 
-176 1 4.934 9.539 0.863 
-177 1 9.267 -9.665 7.957 
-178 1 -3.012 10.419 -6.165 
-179 1 -4.141 -0.091 1.551 
-180 1 -0.339 5.698 -9.229 
-181 1 10.363 4.461 -2.884 
-182 1 6.900 4.868 -6.804 
-183 1 4.552 -0.472 -1.866 
-184 1 6.876 3.478 -10.178 
-185 1 9.684 8.344 2.625 
-186 1 0.249 -2.234 -2.459 
-187 1 -6.357 -6.686 -0.437 
-188 1 -3.223 6.618 -1.686 
-189 1 -6.644 5.362 5.063 
-190 1 -3.869 7.343 9.692 
-191 1 -4.191 6.971 2.585 
-192 1 9.305 -3.647 -7.356 
-193 1 0.066 -4.113 7.059 
-194 1 -4.309 4.115 -9.102 
-195 1 10.242 2.799 8.724 
-196 1 -8.592 2.158 6.260 
-197 1 7.207 -9.020 -9.948 
-198 1 5.075 -1.963 1.695 
-199 1 -5.336 -5.038 9.564 
-200 1 -3.072 -7.420 0.817 
diff --git a/illustration/Equation-of-state/lammps_tau1.25/input.lmp b/illustration/Equation-of-state/lammps_tau1.25/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau1.25/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau1.25/pressure.dat b/illustration/Equation-of-state/lammps_tau1.25/pressure.dat
deleted file mode 100644
index 47c8d9e..0000000
--- a/illustration/Equation-of-state/lammps_tau1.25/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 3345.63
-1000 3339.93
-2000 3708.5
-3000 3482.57
-4000 3138.34
-5000 3175.71
-6000 3504.8
-7000 3745.13
-8000 3433.7
-9000 3452.06
-10000 3301.69
-11000 3811.6
-12000 3448.16
-13000 3650.8
-14000 3647.62
-15000 3808.16
-16000 3149.25
-17000 3387.94
-18000 3176.44
-19000 3852.99
-20000 3391
diff --git a/illustration/Equation-of-state/lammps_tau1.25/variable.lammps b/illustration/Equation-of-state/lammps_tau1.25/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau1.25/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/lammps_tau1.62/Epot.dat b/illustration/Equation-of-state/lammps_tau1.62/Epot.dat
deleted file mode 100644
index 9d4fb48..0000000
--- a/illustration/Equation-of-state/lammps_tau1.62/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 -161.659
-1000 -166.746
-2000 -158.552
-3000 -162.479
-4000 -161.339
-5000 -154.608
-6000 -146.889
-7000 -148.508
-8000 -150.265
-9000 -153.669
-10000 -155.457
-11000 -136.478
-12000 -144.428
-13000 -155.605
-14000 -152.171
-15000 -153.593
-16000 -157.13
-17000 -157.888
-18000 -150.36
-19000 -148.277
-20000 -153.747
diff --git a/illustration/Equation-of-state/lammps_tau1.62/PARM.lammps b/illustration/Equation-of-state/lammps_tau1.62/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau1.62/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau1.62/initial.data b/illustration/Equation-of-state/lammps_tau1.62/initial.data
deleted file mode 100644
index c5ea2ad..0000000
--- a/illustration/Equation-of-state/lammps_tau1.62/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--11.693 11.693 xlo xhi
--11.693 11.693 ylo yhi
--11.693 11.693 zlo zhi
-
-Atoms
-
-1 1 -8.867 -6.287 6.732 
-2 1 8.220 9.302 5.062 
-3 1 6.406 -8.219 -1.742 
-4 1 -5.765 3.748 8.598 
-5 1 10.961 -6.491 8.123 
-6 1 -8.410 -1.495 -0.773 
-7 1 -1.466 2.342 -8.114 
-8 1 0.513 2.599 9.165 
-9 1 11.607 2.571 4.160 
-10 1 -4.468 3.878 4.112 
-11 1 8.663 -3.401 7.833 
-12 1 5.744 11.599 8.136 
-13 1 3.796 -11.250 -3.694 
-14 1 -1.454 -5.450 -4.418 
-15 1 5.719 -7.032 9.526 
-16 1 -6.373 8.285 -0.891 
-17 1 1.975 -2.234 -0.670 
-18 1 8.898 7.568 -9.956 
-19 1 -1.368 7.928 2.167 
-20 1 10.010 -8.179 -8.768 
-21 1 -9.708 -3.450 4.770 
-22 1 -2.555 5.003 7.914 
-23 1 -11.016 -0.397 -5.844 
-24 1 -9.720 -10.086 -0.675 
-25 1 -11.257 -3.778 -4.749 
-26 1 -4.843 9.701 7.607 
-27 1 6.465 -5.781 6.235 
-28 1 0.808 -11.479 -0.298 
-29 1 5.387 7.310 4.578 
-30 1 -9.387 -9.415 -7.448 
-31 1 9.808 -8.849 0.246 
-32 1 7.831 6.600 9.832 
-33 1 10.318 8.079 -6.651 
-34 1 7.755 7.078 -3.771 
-35 1 -8.776 3.667 -5.485 
-36 1 -11.082 -10.533 3.413 
-37 1 11.663 4.857 -9.756 
-38 1 3.508 -10.367 -10.272 
-39 1 -9.721 1.842 -9.390 
-40 1 5.126 1.741 -8.862 
-41 1 -8.591 -5.550 -2.362 
-42 1 -1.395 -7.626 10.110 
-43 1 3.507 1.557 7.928 
-44 1 -1.862 -10.940 -2.075 
-45 1 -6.161 7.124 -8.571 
-46 1 10.331 0.671 11.650 
-47 1 2.003 -8.963 -6.564 
-48 1 -11.427 7.545 7.506 
-49 1 -3.872 -9.946 4.137 
-50 1 6.679 -1.989 -10.994 
-51 1 4.065 6.713 -3.391 
-52 1 7.618 1.230 -5.857 
-53 1 1.464 -3.691 -6.410 
-54 1 -9.412 10.306 -9.373 
-55 1 -6.663 -9.506 11.641 
-56 1 2.646 -10.626 6.560 
-57 1 -1.455 -1.440 -9.228 
-58 1 -0.384 0.385 2.228 
-59 1 2.950 7.881 1.719 
-60 1 -5.642 -7.035 3.513 
-61 1 -6.102 4.831 0.282 
-62 1 -8.104 9.710 -3.868 
-63 1 -0.213 -8.116 -2.661 
-64 1 10.675 10.942 -9.711 
-65 1 2.649 -8.313 -0.554 
-66 1 -2.564 11.201 5.859 
-67 1 3.290 3.384 -1.830 
-68 1 5.909 6.360 -0.382 
-69 1 11.564 8.310 11.129 
-70 1 -3.035 -3.578 10.544 
-71 1 -3.155 3.434 -2.580 
-72 1 9.251 -3.746 -0.864 
-73 1 -9.809 -6.560 -5.375 
-74 1 -11.341 -7.594 -2.365 
-75 1 5.657 1.734 5.312 
-76 1 -0.054 11.393 -6.199 
-77 1 6.443 -10.776 -5.889 
-78 1 -0.964 0.632 -1.734 
-79 1 1.738 9.386 -9.621 
-80 1 -5.619 -3.937 -5.799 
-81 1 6.583 10.282 -2.149 
-82 1 5.114 8.012 11.436 
-83 1 3.180 4.783 -9.321 
-84 1 3.310 10.580 10.441 
-85 1 0.656 3.438 -5.386 
-86 1 -9.751 -3.511 1.505 
-87 1 -1.645 3.588 2.157 
-88 1 -6.486 -10.999 6.281 
-89 1 1.393 -5.104 4.112 
-90 1 5.172 -7.288 -8.910 
-91 1 -4.461 0.636 5.517 
-92 1 3.980 3.066 -5.021 
-93 1 3.306 -9.787 2.762 
-94 1 0.145 -8.174 2.051 
-95 1 -2.773 3.247 11.554 
-96 1 -0.478 8.173 -7.444 
-97 1 -10.967 5.714 2.236 
-98 1 -3.831 -9.603 -4.895 
-99 1 -5.028 -10.936 -1.403 
-100 1 8.991 -1.281 2.873 
-101 1 8.513 -0.565 -8.676 
-102 1 8.386 1.569 7.846 
-103 1 7.547 -11.434 -8.944 
-104 1 0.247 -8.502 -10.368 
-105 1 -5.238 -10.241 -8.064 
-106 1 -4.150 -6.639 8.978 
-107 1 1.902 -1.920 8.403 
-108 1 -10.174 2.453 0.130 
-109 1 -1.052 -3.725 -1.183 
-110 1 3.246 -1.180 -11.288 
-111 1 -3.239 10.549 -7.856 
-112 1 -7.987 -1.011 7.263 
-113 1 10.160 -3.076 -11.134 
-114 1 8.123 -5.712 -11.575 
-115 1 -6.852 6.730 -5.076 
-116 1 11.090 -6.246 4.393 
-117 1 -7.187 -10.227 2.501 
-118 1 -10.623 10.276 -1.556 
-119 1 -9.561 1.268 10.356 
-120 1 -0.957 -8.826 5.894 
-121 1 2.316 5.801 10.656 
-122 1 8.005 -5.707 1.839 
-123 1 -7.633 -6.463 -8.778 
-124 1 -6.544 1.756 -1.027 
-125 1 -3.275 -4.344 4.227 
-126 1 10.457 -1.041 -2.259 
-127 1 -7.457 1.071 2.664 
-128 1 4.817 -5.825 2.793 
-129 1 -6.203 -4.189 1.537 
-130 1 0.680 9.534 8.426 
-131 1 -8.455 -6.669 10.499 
-132 1 -11.542 -6.928 -11.185 
-133 1 -9.903 10.267 5.727 
-134 1 9.211 8.600 -0.223 
-135 1 8.567 5.538 3.802 
-136 1 1.802 -8.388 9.560 
-137 1 -7.627 -1.595 -4.406 
-138 1 -10.516 -9.715 10.276 
-139 1 2.417 1.046 4.683 
-140 1 -8.648 9.483 10.100 
-141 1 -7.758 -10.118 -3.419 
-142 1 5.162 9.831 -8.542 
-143 1 5.823 -4.725 -0.667 
-144 1 -1.149 7.680 6.148 
-145 1 -4.857 -1.389 -2.307 
-146 1 4.548 -3.350 -8.074 
-147 1 3.008 -7.124 5.904 
-148 1 -4.790 0.834 -4.689 
-149 1 0.119 9.423 -2.795 
-150 1 1.059 10.719 3.929 
-151 1 -2.376 -11.389 1.743 
-152 1 3.583 -4.479 -11.185 
-153 1 8.253 -8.556 3.962 
-154 1 -0.476 -1.924 5.250 
-155 1 4.897 -3.164 9.209 
-156 1 7.206 -11.587 3.268 
-157 1 -3.073 -0.383 8.845 
-158 1 -0.415 5.413 -0.382 
-159 1 9.063 -7.565 -4.886 
-160 1 -6.453 -3.403 -10.991 
-161 1 8.355 3.493 -2.529 
-162 1 -10.206 -0.299 3.484 
-163 1 -8.907 8.573 1.887 
-164 1 -8.424 5.919 7.730 
-165 1 3.875 4.170 1.772 
-166 1 -9.807 -7.146 1.312 
-167 1 -5.346 -3.361 6.799 
-168 1 -1.360 -7.674 -7.458 
-169 1 -1.335 10.558 11.502 
-170 1 3.818 7.656 -6.617 
-171 1 6.334 2.348 10.783 
-172 1 11.549 -0.787 7.927 
-173 1 0.492 4.175 5.011 
-174 1 -5.343 -6.218 -3.023 
-175 1 3.450 9.631 5.670 
-176 1 4.517 10.751 0.959 
-177 1 9.988 -9.941 7.085 
-178 1 -4.785 9.836 -4.633 
-179 1 -4.758 -1.152 2.691 
-180 1 -1.007 7.224 -11.020 
-181 1 11.127 4.980 -5.427 
-182 1 6.893 5.952 -7.303 
-183 1 4.957 0.116 -3.108 
-184 1 8.136 4.039 -10.660 
-185 1 11.191 9.703 2.399 
-186 1 -1.563 -1.749 -5.222 
-187 1 -6.723 -8.279 -0.338 
-188 1 -3.256 8.252 -1.668 
-189 1 -7.911 6.299 4.368 
-190 1 -4.280 8.821 10.599 
-191 1 -4.269 9.272 2.969 
-192 1 9.184 -4.851 -7.123 
-193 1 -0.034 -5.092 7.731 
-194 1 -5.433 4.917 -11.077 
-195 1 11.235 3.524 7.899 
-196 1 -8.530 2.593 6.165 
-197 1 8.267 -10.669 10.797 
-198 1 4.134 0.059 0.726 
-199 1 -3.815 -7.687 -10.991 
-200 1 -3.655 -7.098 0.808 
diff --git a/illustration/Equation-of-state/lammps_tau1.62/input.lmp b/illustration/Equation-of-state/lammps_tau1.62/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau1.62/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau1.62/pressure.dat b/illustration/Equation-of-state/lammps_tau1.62/pressure.dat
deleted file mode 100644
index 9cc3422..0000000
--- a/illustration/Equation-of-state/lammps_tau1.62/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 1368.24
-1000 1274.8
-2000 1476.07
-3000 1466.03
-4000 1440.6
-5000 1611.91
-6000 1841
-7000 1728.64
-8000 1665.18
-9000 1555.48
-10000 1506.45
-11000 2010.3
-12000 1824.38
-13000 1492.1
-14000 1632.25
-15000 1569.71
-16000 1466.72
-17000 1431.24
-18000 1624.3
-19000 1730.38
-20000 1540.17
diff --git a/illustration/Equation-of-state/lammps_tau1.62/variable.lammps b/illustration/Equation-of-state/lammps_tau1.62/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau1.62/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/lammps_tau2.1/Epot.dat b/illustration/Equation-of-state/lammps_tau2.1/Epot.dat
deleted file mode 100644
index 02ada2f..0000000
--- a/illustration/Equation-of-state/lammps_tau2.1/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 -129.147
-1000 -125.045
-2000 -131.071
-3000 -129.733
-4000 -128.499
-5000 -129.705
-6000 -130.73
-7000 -129.654
-8000 -123.251
-9000 -126
-10000 -122.864
-11000 -113.039
-12000 -125.704
-13000 -124.905
-14000 -118.59
-15000 -121.527
-16000 -118.126
-17000 -119.716
-18000 -120.984
-19000 -113.821
-20000 -129.797
diff --git a/illustration/Equation-of-state/lammps_tau2.1/PARM.lammps b/illustration/Equation-of-state/lammps_tau2.1/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau2.1/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau2.1/initial.data b/illustration/Equation-of-state/lammps_tau2.1/initial.data
deleted file mode 100644
index 83620e7..0000000
--- a/illustration/Equation-of-state/lammps_tau2.1/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--12.750 12.750 xlo xhi
--12.750 12.750 ylo yhi
--12.750 12.750 zlo zhi
-
-Atoms
-
-1 1 -8.776 -7.879 6.382 
-2 1 9.376 11.311 5.522 
-3 1 5.960 -12.723 -0.052 
-4 1 -6.180 3.920 8.367 
-5 1 12.334 -6.881 10.087 
-6 1 -8.717 -2.423 -0.323 
-7 1 -1.554 1.274 -7.986 
-8 1 -0.670 3.611 9.183 
-9 1 -11.798 3.312 4.302 
-10 1 -5.986 4.310 3.974 
-11 1 10.719 -3.063 7.462 
-12 1 6.802 -12.544 8.218 
-13 1 3.617 12.607 -4.966 
-14 1 -2.436 -3.964 -5.549 
-15 1 6.792 -8.868 6.944 
-16 1 -6.827 7.878 -1.859 
-17 1 2.714 -0.167 0.152 
-18 1 9.769 7.710 -11.483 
-19 1 -1.714 10.269 2.017 
-20 1 -10.345 -7.238 -10.190 
-21 1 -10.583 -4.544 4.200 
-22 1 -4.039 6.426 9.881 
-23 1 12.386 0.298 -5.781 
-24 1 -10.666 -10.270 0.525 
-25 1 -11.481 -4.725 -4.855 
-26 1 -5.538 10.983 8.794 
-27 1 8.589 -5.504 7.350 
-28 1 -0.729 12.547 -0.535 
-29 1 3.115 9.424 4.858 
-30 1 -11.012 -9.877 -6.147 
-31 1 11.130 -10.599 0.890 
-32 1 9.656 6.192 10.865 
-33 1 12.641 10.193 -7.949 
-34 1 7.547 5.814 -4.813 
-35 1 -10.868 6.821 -7.183 
-36 1 -10.837 -12.687 4.261 
-37 1 11.764 4.941 -12.503 
-38 1 4.711 -12.184 -11.845 
-39 1 12.141 3.619 -8.831 
-40 1 3.548 1.575 -7.338 
-41 1 -9.030 -6.649 -3.813 
-42 1 0.145 -5.983 9.992 
-43 1 1.922 0.520 8.927 
-44 1 -1.466 -12.353 -3.518 
-45 1 -6.700 11.053 -9.862 
-46 1 10.273 1.354 -11.199 
-47 1 1.620 -10.443 -8.075 
-48 1 -12.113 10.777 10.355 
-49 1 -4.723 -10.344 4.616 
-50 1 5.746 -3.291 -11.673 
-51 1 4.902 7.052 -2.861 
-52 1 7.336 2.238 -7.094 
-53 1 0.884 -1.317 -6.288 
-54 1 -10.389 10.100 -11.073 
-55 1 -6.945 -10.125 -11.395 
-56 1 2.618 12.550 6.774 
-57 1 -2.094 -3.749 -9.456 
-58 1 -1.713 -2.109 1.774 
-59 1 2.344 9.994 0.365 
-60 1 -6.896 -8.719 2.491 
-61 1 -5.222 4.175 -0.337 
-62 1 -7.915 11.712 -3.112 
-63 1 0.714 -9.211 -4.307 
-64 1 11.835 11.147 -11.426 
-65 1 3.123 -8.655 0.035 
-66 1 -2.944 12.141 7.018 
-67 1 4.286 3.935 -1.721 
-68 1 7.774 7.572 -0.781 
-69 1 9.770 9.798 10.598 
-70 1 -4.009 -4.153 11.291 
-71 1 -3.057 3.276 -3.370 
-72 1 8.095 -3.980 -1.800 
-73 1 -10.208 -6.811 -6.843 
-74 1 -11.801 -8.168 -1.575 
-75 1 7.675 2.566 4.821 
-76 1 1.418 10.876 -8.456 
-77 1 8.284 11.933 -7.226 
-78 1 1.920 1.280 -2.987 
-79 1 3.718 10.056 -10.802 
-80 1 -5.399 -5.751 -6.657 
-81 1 6.502 9.861 -4.192 
-82 1 5.537 8.035 10.737 
-83 1 4.332 6.356 -9.324 
-84 1 3.013 10.614 11.040 
-85 1 1.442 3.581 -8.959 
-86 1 -9.938 -6.278 1.445 
-87 1 -2.079 5.219 3.102 
-88 1 -7.009 11.419 4.934 
-89 1 1.936 -6.072 4.036 
-90 1 5.724 -8.532 -8.717 
-91 1 -6.048 0.729 5.610 
-92 1 3.698 4.046 -4.989 
-93 1 5.924 -10.280 3.239 
-94 1 0.827 -10.095 2.149 
-95 1 -1.903 1.548 12.453 
-96 1 -2.110 11.364 -6.783 
-97 1 -12.665 6.978 2.944 
-98 1 -4.654 -12.670 -2.561 
-99 1 -3.943 9.761 -4.067 
-100 1 10.288 -3.386 2.449 
-101 1 8.900 -0.857 -8.338 
-102 1 9.504 2.993 9.015 
-103 1 7.669 10.965 -10.528 
-104 1 -0.389 -9.621 -11.924 
-105 1 -9.287 -10.559 -9.380 
-106 1 -4.659 -5.519 7.919 
-107 1 -0.537 -2.648 9.630 
-108 1 -8.775 4.976 1.739 
-109 1 -2.355 -5.891 -1.131 
-110 1 4.199 1.305 -10.842 
-111 1 -2.644 -12.285 -9.568 
-112 1 -8.132 -1.492 7.995 
-113 1 10.326 -6.341 -9.405 
-114 1 8.927 -4.929 12.562 
-115 1 -9.278 9.753 -6.057 
-116 1 -12.574 -6.629 6.447 
-117 1 -6.186 -12.012 1.301 
-118 1 -11.138 -12.408 -2.487 
-119 1 -11.489 3.534 10.884 
-120 1 -0.705 -10.988 5.392 
-121 1 1.440 8.076 8.539 
-122 1 9.836 -7.614 2.524 
-123 1 -7.065 -8.469 -7.903 
-124 1 -7.657 0.677 0.916 
-125 1 -2.886 -3.924 4.844 
-126 1 12.394 -1.925 -2.856 
-127 1 -11.670 -0.888 1.071 
-128 1 5.683 -6.032 3.634 
-129 1 -6.547 -1.796 3.262 
-130 1 -0.776 10.376 10.493 
-131 1 -9.755 -8.487 12.205 
-132 1 11.908 -9.242 -12.293 
-133 1 -10.781 9.954 5.903 
-134 1 11.024 9.975 -0.932 
-135 1 8.784 7.940 4.223 
-136 1 2.902 -9.567 9.524 
-137 1 -5.474 -3.126 -2.954 
-138 1 -11.542 -9.881 9.917 
-139 1 3.399 3.422 2.250 
-140 1 -9.008 12.150 8.766 
-141 1 -7.233 -10.861 -4.623 
-142 1 4.439 10.203 -7.717 
-143 1 5.582 -5.129 0.009 
-144 1 -2.450 8.499 7.808 
-145 1 -2.326 0.817 -1.204 
-146 1 4.657 -4.744 -8.012 
-147 1 2.644 -9.258 4.828 
-148 1 -5.720 0.676 -4.104 
-149 1 -0.668 9.728 -2.816 
-150 1 0.304 10.562 5.110 
-151 1 -2.679 -11.491 2.549 
-152 1 5.808 -6.710 -11.830 
-153 1 9.580 -10.618 4.233 
-154 1 -0.624 0.751 3.521 
-155 1 5.070 -5.394 10.074 
-156 1 7.337 11.894 3.128 
-157 1 -5.206 -0.021 9.837 
-158 1 0.537 5.790 0.863 
-159 1 9.694 -6.068 -5.533 
-160 1 -6.552 -4.235 -11.465 
-161 1 9.840 4.034 -1.287 
-162 1 -12.290 0.124 4.509 
-163 1 -10.095 9.524 1.932 
-164 1 -9.518 7.868 8.075 
-165 1 4.813 7.127 1.335 
-166 1 -11.713 -8.109 3.610 
-167 1 -2.964 -0.985 6.944 
-168 1 -1.292 -8.147 -7.129 
-169 1 -3.382 8.181 12.676 
-170 1 2.896 7.935 -5.638 
-171 1 7.024 1.627 11.722 
-172 1 -11.828 -1.569 7.442 
-173 1 1.098 4.882 5.141 
-174 1 -5.594 -7.451 -3.888 
-175 1 6.055 10.352 6.144 
-176 1 3.217 12.503 3.342 
-177 1 11.471 -9.875 7.537 
-178 1 -5.079 -12.352 -7.041 
-179 1 -4.117 1.611 2.473 
-180 1 -0.150 6.938 12.353 
-181 1 12.155 4.953 -5.459 
-182 1 8.652 6.319 -8.895 
-183 1 5.679 0.858 -3.488 
-184 1 7.190 3.549 -10.363 
-185 1 11.462 10.604 2.705 
-186 1 0.332 -3.115 -2.674 
-187 1 -7.803 -9.733 -0.970 
-188 1 -4.307 9.721 -0.601 
-189 1 -8.054 7.622 4.778 
-190 1 -4.591 11.897 12.200 
-191 1 -4.908 8.355 3.276 
-192 1 11.884 -3.536 -7.070 
-193 1 -0.964 -7.489 6.617 
-194 1 -5.396 4.705 12.729 
-195 1 12.404 4.614 7.010 
-196 1 -9.531 3.015 7.282 
-197 1 9.344 -10.974 10.847 
-198 1 3.622 -0.114 3.452 
-199 1 -3.727 -7.345 -10.654 
-200 1 -3.627 -9.707 -0.418 
diff --git a/illustration/Equation-of-state/lammps_tau2.1/input.lmp b/illustration/Equation-of-state/lammps_tau2.1/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau2.1/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau2.1/pressure.dat b/illustration/Equation-of-state/lammps_tau2.1/pressure.dat
deleted file mode 100644
index ff4379a..0000000
--- a/illustration/Equation-of-state/lammps_tau2.1/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 931.705
-1000 892.275
-2000 763.933
-3000 737.452
-4000 835.726
-5000 833.305
-6000 805.903
-7000 822.582
-8000 936.579
-9000 832.251
-10000 888.815
-11000 1127.03
-12000 926.519
-13000 931.196
-14000 1074.46
-15000 979.989
-16000 1020.01
-17000 1060.53
-18000 1014.67
-19000 1051.18
-20000 671.399
diff --git a/illustration/Equation-of-state/lammps_tau2.1/variable.lammps b/illustration/Equation-of-state/lammps_tau2.1/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau2.1/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/lammps_tau2.72/Epot.dat b/illustration/Equation-of-state/lammps_tau2.72/Epot.dat
deleted file mode 100644
index 2e585b7..0000000
--- a/illustration/Equation-of-state/lammps_tau2.72/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 -96.1255
-1000 -98.4006
-2000 -101.411
-3000 -97.7504
-4000 -97.3302
-5000 -100.904
-6000 -101.638
-7000 -101.48
-8000 -99.5857
-9000 -101.136
-10000 -89.6301
-11000 -93.9277
-12000 -95.968
-13000 -101.609
-14000 -101.31
-15000 -96.3495
-16000 -95.5773
-17000 -90.3194
-18000 -96.9751
-19000 -96.8575
-20000 -101.15
diff --git a/illustration/Equation-of-state/lammps_tau2.72/PARM.lammps b/illustration/Equation-of-state/lammps_tau2.72/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau2.72/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau2.72/initial.data b/illustration/Equation-of-state/lammps_tau2.72/initial.data
deleted file mode 100644
index 33b2975..0000000
--- a/illustration/Equation-of-state/lammps_tau2.72/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--13.898 13.898 xlo xhi
--13.898 13.898 ylo yhi
--13.898 13.898 zlo zhi
-
-Atoms
-
-1 1 -9.049 -7.546 6.537 
-2 1 9.115 11.990 6.069 
-3 1 4.783 -12.635 1.061 
-4 1 -6.881 5.072 8.854 
-5 1 -12.932 -8.489 9.476 
-6 1 -10.639 -3.450 -1.162 
-7 1 -1.701 1.072 -9.628 
-8 1 -0.014 1.480 11.162 
-9 1 -10.924 4.217 5.928 
-10 1 -6.849 3.904 4.670 
-11 1 10.089 -3.582 8.181 
-12 1 6.901 -13.614 9.147 
-13 1 5.166 13.070 -3.275 
-14 1 -3.306 -6.868 -5.552 
-15 1 6.944 -9.529 7.432 
-16 1 -6.756 9.299 -0.909 
-17 1 1.760 -1.122 0.738 
-18 1 7.562 9.546 -11.124 
-19 1 -1.173 12.118 2.148 
-20 1 -12.158 -10.356 -11.057 
-21 1 -12.409 -3.923 4.257 
-22 1 -2.937 4.467 9.576 
-23 1 13.023 0.155 -6.551 
-24 1 -12.379 -10.945 1.622 
-25 1 -13.026 -5.857 -6.768 
-26 1 -6.623 12.507 8.169 
-27 1 9.620 -6.874 7.114 
-28 1 0.697 13.304 -1.202 
-29 1 6.848 9.496 5.858 
-30 1 -9.221 -9.813 -8.351 
-31 1 11.806 -10.842 1.867 
-32 1 11.673 7.207 12.907 
-33 1 12.247 11.836 -9.279 
-34 1 8.942 6.206 -4.952 
-35 1 -11.851 6.068 -7.302 
-36 1 -12.188 -12.639 6.620 
-37 1 -13.693 4.096 13.550 
-38 1 4.532 13.106 -11.852 
-39 1 12.496 4.811 -9.294 
-40 1 6.987 -0.172 -6.261 
-41 1 -11.198 -8.063 -3.337 
-42 1 -0.520 -7.909 11.106 
-43 1 2.872 -0.724 9.696 
-44 1 -1.877 -12.411 -3.233 
-45 1 -6.744 12.252 -12.471 
-46 1 11.308 2.119 -11.429 
-47 1 1.327 -10.513 -7.812 
-48 1 -10.526 9.926 9.293 
-49 1 -5.177 -11.435 4.523 
-50 1 5.849 -2.713 -13.755 
-51 1 3.101 8.589 -3.527 
-52 1 8.660 2.559 -8.382 
-53 1 0.424 -2.884 -6.782 
-54 1 -11.398 11.140 -12.452 
-55 1 -9.226 -13.010 -7.434 
-56 1 3.437 -12.634 6.577 
-57 1 -2.673 -3.563 -10.057 
-58 1 -2.760 -1.971 3.014 
-59 1 2.557 10.914 1.399 
-60 1 -6.331 -8.767 2.362 
-61 1 -5.789 5.509 0.009 
-62 1 -8.949 13.394 -2.735 
-63 1 -2.454 -9.237 -2.838 
-64 1 10.530 -13.556 -12.441 
-65 1 2.170 -7.802 -0.613 
-66 1 -2.533 11.408 7.965 
-67 1 3.197 4.450 -2.629 
-68 1 5.557 10.314 -0.945 
-69 1 -13.829 9.790 10.753 
-70 1 -4.035 -4.911 13.888 
-71 1 -2.878 3.033 -3.447 
-72 1 7.844 -3.708 -3.018 
-73 1 -10.213 -7.372 -6.204 
-74 1 13.671 -8.714 -0.602 
-75 1 8.342 3.440 5.631 
-76 1 1.038 11.762 -6.414 
-77 1 8.142 11.572 -7.524 
-78 1 0.514 2.012 -1.156 
-79 1 3.858 10.256 -13.352 
-80 1 -7.545 -6.081 -3.915 
-81 1 8.868 9.857 -3.413 
-82 1 6.899 9.070 11.995 
-83 1 6.361 6.794 -9.067 
-84 1 3.946 12.647 12.175 
-85 1 2.850 3.505 -8.555 
-86 1 -12.754 -6.343 1.692 
-87 1 -1.248 4.734 3.414 
-88 1 -8.211 -13.733 5.706 
-89 1 1.387 -7.321 3.684 
-90 1 5.770 -10.124 -11.922 
-91 1 -7.924 0.744 5.695 
-92 1 5.966 3.959 -4.416 
-93 1 6.300 -12.583 4.053 
-94 1 -1.570 -11.976 0.266 
-95 1 -3.776 2.181 -13.262 
-96 1 -0.798 -13.247 -7.926 
-97 1 -13.667 5.705 3.780 
-98 1 -4.733 -12.896 -5.124 
-99 1 -5.067 13.789 -1.857 
-100 1 11.934 -3.063 3.230 
-101 1 10.465 -0.951 -9.707 
-102 1 9.868 4.667 10.023 
-103 1 8.022 13.052 -10.118 
-104 1 0.800 -11.160 -11.991 
-105 1 -7.019 -11.462 -13.581 
-106 1 -4.615 -7.162 8.036 
-107 1 -0.192 -3.216 9.676 
-108 1 -9.957 2.268 2.348 
-109 1 -0.369 -5.205 0.078 
-110 1 2.632 0.142 -13.043 
-111 1 -3.384 -12.921 -10.205 
-112 1 -9.243 -2.157 9.500 
-113 1 11.763 -5.346 -13.261 
-114 1 10.168 -6.923 10.975 
-115 1 -8.480 10.555 -5.046 
-116 1 13.040 -7.945 4.578 
-117 1 -7.086 -12.666 2.062 
-118 1 -9.938 -13.842 0.650 
-119 1 -11.549 2.369 11.551 
-120 1 -1.370 13.824 5.860 
-121 1 2.825 9.430 10.446 
-122 1 9.027 -9.993 4.086 
-123 1 -6.715 -7.436 -7.758 
-124 1 -7.924 1.808 -0.268 
-125 1 -2.640 -6.815 5.319 
-126 1 12.759 -2.309 -2.210 
-127 1 -13.138 -1.765 1.570 
-128 1 4.929 -8.518 3.043 
-129 1 -6.720 -2.474 5.473 
-130 1 -0.659 10.162 11.294 
-131 1 -9.693 -6.601 -10.291 
-132 1 -12.449 -11.345 13.418 
-133 1 12.855 11.200 6.625 
-134 1 13.297 11.288 1.677 
-135 1 9.211 9.883 1.056 
-136 1 2.842 -10.328 9.893 
-137 1 -3.225 -0.894 -5.729 
-138 1 12.706 -12.080 11.430 
-139 1 4.960 4.629 2.308 
-140 1 -10.174 13.285 10.183 
-141 1 -8.131 -11.190 -3.953 
-142 1 4.370 12.332 -6.878 
-143 1 5.975 -5.267 -0.622 
-144 1 -4.465 12.533 5.424 
-145 1 -2.547 0.018 -1.017 
-146 1 5.705 -4.299 -10.233 
-147 1 3.107 -8.909 5.741 
-148 1 -6.326 2.094 -5.409 
-149 1 -1.036 11.087 -3.158 
-150 1 1.434 10.303 5.275 
-151 1 -2.253 -11.304 3.747 
-152 1 4.881 -5.982 -13.541 
-153 1 12.142 -11.451 5.484 
-154 1 -0.496 0.137 4.534 
-155 1 5.293 -6.759 10.369 
-156 1 8.374 12.884 2.917 
-157 1 -4.587 1.544 7.374 
-158 1 1.882 6.471 1.096 
-159 1 10.005 -7.013 -4.320 
-160 1 -6.882 -4.253 -11.827 
-161 1 7.257 6.270 -1.767 
-162 1 -11.489 -0.155 6.005 
-163 1 -10.462 7.449 2.179 
-164 1 -10.817 6.354 8.846 
-165 1 6.059 7.983 1.346 
-166 1 -9.818 -7.499 2.748 
-167 1 -5.112 -1.481 8.781 
-168 1 -2.267 -10.008 -7.126 
-169 1 -1.666 10.249 -13.101 
-170 1 4.814 8.689 -6.837 
-171 1 9.003 2.169 12.960 
-172 1 13.229 -2.123 8.240 
-173 1 2.435 5.446 5.829 
-174 1 -4.660 -6.362 -1.881 
-175 1 4.903 11.894 4.486 
-176 1 1.543 -13.816 3.160 
-177 1 11.117 -11.048 8.388 
-178 1 -5.538 11.541 -8.429 
-179 1 -4.734 1.902 2.797 
-180 1 -1.474 7.078 13.792 
-181 1 13.007 4.790 -5.509 
-182 1 9.703 6.968 -12.353 
-183 1 8.398 0.464 -3.100 
-184 1 7.874 3.847 -11.662 
-185 1 -10.231 11.794 3.512 
-186 1 -1.210 -4.280 -3.712 
-187 1 -10.865 -11.097 -1.315 
-188 1 -3.796 10.655 0.142 
-189 1 -8.904 7.805 5.916 
-190 1 -4.492 -13.822 12.308 
-191 1 -5.667 8.854 3.817 
-192 1 11.659 -4.473 -5.803 
-193 1 0.388 -6.584 8.048 
-194 1 -6.026 4.309 13.211 
-195 1 13.388 5.813 9.159 
-196 1 -10.242 2.224 7.967 
-197 1 8.518 -11.134 11.810 
-198 1 5.023 -0.302 3.129 
-199 1 -3.613 -9.186 -11.250 
-200 1 -4.933 -10.670 0.076 
diff --git a/illustration/Equation-of-state/lammps_tau2.72/input.lmp b/illustration/Equation-of-state/lammps_tau2.72/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau2.72/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau2.72/pressure.dat b/illustration/Equation-of-state/lammps_tau2.72/pressure.dat
deleted file mode 100644
index 5de3e34..0000000
--- a/illustration/Equation-of-state/lammps_tau2.72/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 706.891
-1000 624.652
-2000 553.787
-3000 631.548
-4000 622.661
-5000 557.007
-6000 476.033
-7000 490.377
-8000 561.301
-9000 598.755
-10000 807.134
-11000 720.798
-12000 698.141
-13000 562.511
-14000 495.024
-15000 553.927
-16000 547.054
-17000 605.863
-18000 527.69
-19000 599.136
-20000 520.179
diff --git a/illustration/Equation-of-state/lammps_tau2.72/variable.lammps b/illustration/Equation-of-state/lammps_tau2.72/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau2.72/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/lammps_tau3.52/Epot.dat b/illustration/Equation-of-state/lammps_tau3.52/Epot.dat
deleted file mode 100644
index 768d9cf..0000000
--- a/illustration/Equation-of-state/lammps_tau3.52/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 -86.4968
-1000 -81.7244
-2000 -83.7244
-3000 -81.0985
-4000 -82.6465
-5000 -82.7639
-6000 -78.8906
-7000 -74.9298
-8000 -78.7919
-9000 -71.2612
-10000 -78.9983
-11000 -75.5426
-12000 -75.9957
-13000 -75.6773
-14000 -75.2124
-15000 -73.7487
-16000 -80.5974
-17000 -77.2209
-18000 -76.745
-19000 -74.3314
-20000 -77.712
diff --git a/illustration/Equation-of-state/lammps_tau3.52/PARM.lammps b/illustration/Equation-of-state/lammps_tau3.52/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau3.52/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau3.52/initial.data b/illustration/Equation-of-state/lammps_tau3.52/initial.data
deleted file mode 100644
index a006fdc..0000000
--- a/illustration/Equation-of-state/lammps_tau3.52/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--15.145 15.145 xlo xhi
--15.145 15.145 ylo yhi
--15.145 15.145 zlo zhi
-
-Atoms
-
-1 1 -9.281 -9.529 6.839 
-2 1 11.446 12.912 7.057 
-3 1 6.171 -13.386 -0.960 
-4 1 -7.547 4.170 10.214 
-5 1 -13.689 -8.929 10.583 
-6 1 -13.768 -2.132 -0.953 
-7 1 -2.514 0.730 -9.461 
-8 1 -3.008 4.522 13.130 
-9 1 -11.361 3.604 4.644 
-10 1 -7.234 4.211 5.723 
-11 1 13.620 -5.521 10.139 
-12 1 7.544 -14.579 9.183 
-13 1 5.340 13.343 -1.650 
-14 1 -5.879 -7.636 -2.282 
-15 1 8.595 -10.647 8.114 
-16 1 -7.964 12.786 -0.149 
-17 1 0.304 -3.067 -0.041 
-18 1 9.911 11.554 -13.147 
-19 1 -2.766 10.617 2.421 
-20 1 -12.299 -11.371 -10.378 
-21 1 -14.241 -4.184 6.431 
-22 1 -3.457 4.487 9.332 
-23 1 12.779 -1.480 -7.491 
-24 1 -10.302 -10.798 1.138 
-25 1 -13.615 -6.437 -5.753 
-26 1 -6.838 14.627 9.046 
-27 1 11.023 -7.740 9.051 
-28 1 1.084 15.070 -1.353 
-29 1 7.936 11.003 5.786 
-30 1 -8.036 -11.765 -8.879 
-31 1 -14.420 -11.374 2.909 
-32 1 13.447 7.035 14.435 
-33 1 -15.134 13.350 -8.036 
-34 1 10.910 7.473 -4.143 
-35 1 -13.434 4.962 -7.388 
-36 1 -12.586 14.971 6.189 
-37 1 15.108 2.051 -15.135 
-38 1 2.280 13.783 -12.303 
-39 1 14.874 4.658 -10.499 
-40 1 5.778 1.497 -6.448 
-41 1 -10.655 -8.459 -2.616 
-42 1 1.330 -7.758 10.197 
-43 1 2.720 0.015 10.680 
-44 1 -2.339 -14.406 -2.933 
-45 1 -6.734 13.347 -11.871 
-46 1 10.970 4.076 -10.071 
-47 1 -1.017 -11.350 -8.888 
-48 1 -11.522 12.275 13.273 
-49 1 -4.685 -14.131 4.166 
-50 1 6.851 -2.044 -14.389 
-51 1 5.152 9.992 -4.504 
-52 1 8.325 3.542 -8.264 
-53 1 3.061 -4.099 -7.408 
-54 1 -11.998 12.275 -12.552 
-55 1 -8.431 -14.802 -7.053 
-56 1 2.259 -13.968 7.830 
-57 1 -0.834 -2.259 -9.092 
-58 1 -2.074 -2.934 3.213 
-59 1 1.095 12.570 1.233 
-60 1 -6.927 -10.776 3.473 
-61 1 -8.097 5.889 1.634 
-62 1 -6.990 11.728 -3.252 
-63 1 -2.781 -10.770 -3.464 
-64 1 12.470 -15.054 -14.053 
-65 1 1.558 -9.788 -0.451 
-66 1 -3.473 13.257 6.707 
-67 1 4.167 3.253 -3.277 
-68 1 5.757 8.499 -1.314 
-69 1 12.979 10.768 12.830 
-70 1 -5.627 -5.851 14.210 
-71 1 -4.631 2.941 -2.852 
-72 1 9.200 -5.657 -2.974 
-73 1 -11.202 -8.389 -6.481 
-74 1 -15.021 -9.614 -3.698 
-75 1 8.487 4.449 5.284 
-76 1 -0.100 12.048 -7.877 
-77 1 7.203 9.007 -7.261 
-78 1 -2.252 -0.192 -1.143 
-79 1 3.085 11.269 -14.742 
-80 1 -9.264 -5.483 -3.637 
-81 1 9.027 10.254 -2.553 
-82 1 6.966 10.223 12.766 
-83 1 4.779 10.336 -10.011 
-84 1 3.922 14.268 13.744 
-85 1 3.917 2.320 -9.762 
-86 1 -12.283 -4.925 3.066 
-87 1 -2.472 3.746 3.838 
-88 1 -8.575 -13.846 5.909 
-89 1 0.031 -8.133 4.020 
-90 1 5.558 -10.888 -11.989 
-91 1 -6.732 0.907 7.322 
-92 1 5.519 5.660 -4.728 
-93 1 5.858 15.021 2.086 
-94 1 -0.321 -12.033 0.921 
-95 1 -5.029 2.276 -14.472 
-96 1 -1.099 -14.154 -10.763 
-97 1 -12.430 6.001 -0.512 
-98 1 -5.163 -13.188 -5.580 
-99 1 -5.852 -15.001 -2.098 
-100 1 11.909 -3.338 3.203 
-101 1 9.878 0.379 -10.549 
-102 1 9.797 6.562 13.837 
-103 1 8.874 -14.849 -13.268 
-104 1 0.295 -10.140 -12.272 
-105 1 -7.560 -14.099 -13.651 
-106 1 -4.925 -7.345 8.018 
-107 1 -0.286 -2.420 10.986 
-108 1 -12.653 6.926 4.842 
-109 1 -3.633 -4.468 -1.086 
-110 1 3.604 -0.157 -14.424 
-111 1 -4.697 -13.130 -10.283 
-112 1 -10.911 -1.328 8.691 
-113 1 12.840 -6.357 14.863 
-114 1 11.406 -8.847 12.073 
-115 1 -11.312 10.380 -1.986 
-116 1 13.830 -7.937 3.772 
-117 1 -9.312 -13.763 2.412 
-118 1 -11.535 14.190 -1.059 
-119 1 -11.685 1.099 12.301 
-120 1 -1.189 -14.383 5.187 
-121 1 2.480 8.627 11.928 
-122 1 10.367 -10.374 4.392 
-123 1 -7.416 -8.621 -10.029 
-124 1 -8.594 2.396 0.595 
-125 1 -4.162 -8.231 4.615 
-126 1 14.170 -3.348 -4.485 
-127 1 -11.578 -0.316 2.154 
-128 1 3.897 -7.925 3.552 
-129 1 -8.051 -1.857 5.500 
-130 1 -0.936 9.780 11.280 
-131 1 -10.293 -9.036 -13.539 
-132 1 14.466 -9.430 -12.718 
-133 1 -13.525 10.464 7.023 
-134 1 13.853 13.259 0.291 
-135 1 10.920 10.309 0.938 
-136 1 6.088 -12.594 12.699 
-137 1 -5.715 -2.114 -6.755 
-138 1 12.467 -10.209 14.888 
-139 1 5.322 5.010 1.993 
-140 1 -10.679 14.062 9.842 
-141 1 -8.820 -12.030 -4.687 
-142 1 8.148 12.331 -8.121 
-143 1 6.985 -4.465 -0.432 
-144 1 -6.731 13.620 5.419 
-145 1 -0.622 1.724 1.447 
-146 1 5.737 -2.378 -10.332 
-147 1 4.022 -10.716 7.175 
-148 1 -7.545 1.761 -5.701 
-149 1 -0.053 13.279 -4.292 
-150 1 0.386 11.271 4.838 
-151 1 -2.460 -14.841 1.423 
-152 1 6.760 -7.298 -14.702 
-153 1 12.896 -12.719 5.220 
-154 1 -2.617 -0.349 5.737 
-155 1 7.517 -7.310 10.955 
-156 1 8.443 12.722 1.581 
-157 1 -5.718 0.560 11.424 
-158 1 1.539 8.846 0.809 
-159 1 12.435 -6.794 -6.391 
-160 1 -8.548 -4.923 -14.039 
-161 1 9.336 5.648 -1.830 
-162 1 -12.739 0.502 5.620 
-163 1 -10.608 9.472 3.168 
-164 1 -10.927 7.669 9.066 
-165 1 8.027 8.211 1.900 
-166 1 -11.681 -8.342 4.244 
-167 1 -6.195 -2.266 8.807 
-168 1 -2.528 -9.151 -6.484 
-169 1 -2.257 8.989 -12.523 
-170 1 3.797 8.212 -7.417 
-171 1 9.839 1.725 14.919 
-172 1 12.937 0.255 7.865 
-173 1 2.728 6.917 5.178 
-174 1 -2.269 -6.975 -2.935 
-175 1 5.552 13.448 5.462 
-176 1 2.464 -15.054 4.480 
-177 1 12.567 -12.516 8.248 
-178 1 -4.256 13.571 -8.279 
-179 1 -4.845 1.268 2.058 
-180 1 -0.810 6.576 -14.650 
-181 1 12.742 5.725 -6.820 
-182 1 10.087 7.822 -12.098 
-183 1 9.056 -0.134 -5.778 
-184 1 8.206 3.881 -12.044 
-185 1 -12.602 13.440 2.440 
-186 1 -0.057 -3.631 -5.132 
-187 1 -12.387 -11.675 -1.845 
-188 1 -4.272 9.707 -1.857 
-189 1 -8.042 8.944 6.520 
-190 1 -3.827 14.680 -14.729 
-191 1 -6.355 9.950 1.544 
-192 1 -14.300 -5.055 -8.803 
-193 1 -2.771 -4.472 6.509 
-194 1 -7.582 3.940 14.258 
-195 1 15.044 5.340 10.011 
-196 1 -10.893 3.312 8.364 
-197 1 10.365 -13.426 11.525 
-198 1 4.760 -0.515 2.060 
-199 1 -6.144 -7.558 -13.309 
-200 1 -5.000 -10.494 0.701 
diff --git a/illustration/Equation-of-state/lammps_tau3.52/input.lmp b/illustration/Equation-of-state/lammps_tau3.52/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau3.52/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau3.52/pressure.dat b/illustration/Equation-of-state/lammps_tau3.52/pressure.dat
deleted file mode 100644
index 651eca5..0000000
--- a/illustration/Equation-of-state/lammps_tau3.52/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 316.25
-1000 437.481
-2000 405.325
-3000 424.676
-4000 376.85
-5000 360.7
-6000 308.339
-7000 400.416
-8000 343.638
-9000 454.706
-10000 394.113
-11000 504.971
-12000 485.083
-13000 434.304
-14000 413.118
-15000 421.069
-16000 322.504
-17000 373.537
-18000 354.066
-19000 377.353
-20000 347.605
diff --git a/illustration/Equation-of-state/lammps_tau3.52/variable.lammps b/illustration/Equation-of-state/lammps_tau3.52/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau3.52/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/lammps_tau4.55/Epot.dat b/illustration/Equation-of-state/lammps_tau4.55/Epot.dat
deleted file mode 100644
index 1227779..0000000
--- a/illustration/Equation-of-state/lammps_tau4.55/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 -66.2625
-1000 -66.3232
-2000 -64.1552
-3000 -64.5485
-4000 -64.2757
-5000 -65.5901
-6000 -65.9053
-7000 -63.0458
-8000 -63.1695
-9000 -65.891
-10000 -61.0168
-11000 -64.2449
-12000 -63.1791
-13000 -64.3465
-14000 -62.103
-15000 -60.2522
-16000 -58.5747
-17000 -52.8854
-18000 -59.245
-19000 -61.417
-20000 -58.8275
diff --git a/illustration/Equation-of-state/lammps_tau4.55/PARM.lammps b/illustration/Equation-of-state/lammps_tau4.55/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau4.55/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau4.55/initial.data b/illustration/Equation-of-state/lammps_tau4.55/initial.data
deleted file mode 100644
index 67a2b50..0000000
--- a/illustration/Equation-of-state/lammps_tau4.55/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--16.498 16.498 xlo xhi
--16.498 16.498 ylo yhi
--16.498 16.498 zlo zhi
-
-Atoms
-
-1 1 -10.877 -9.020 7.445 
-2 1 12.164 15.230 9.285 
-3 1 4.921 -13.945 -0.975 
-4 1 -7.065 3.115 10.492 
-5 1 -15.842 -8.939 10.437 
-6 1 -14.156 -2.608 -0.972 
-7 1 -2.217 0.889 -10.475 
-8 1 1.293 6.491 14.724 
-9 1 -12.155 2.439 5.734 
-10 1 -6.845 4.510 6.588 
-11 1 13.984 -6.437 10.718 
-12 1 8.548 -16.282 11.468 
-13 1 4.887 15.877 -5.346 
-14 1 -5.888 -6.614 -4.326 
-15 1 9.944 -11.945 10.986 
-16 1 -8.600 13.701 -0.630 
-17 1 0.343 -1.859 1.018 
-18 1 10.473 12.996 -13.593 
-19 1 -2.244 10.894 2.490 
-20 1 -13.571 -11.625 -11.628 
-21 1 -15.691 -5.299 7.358 
-22 1 -3.942 4.679 12.175 
-23 1 14.908 -1.952 -9.439 
-24 1 -11.725 -11.543 0.243 
-25 1 -15.266 -6.377 -7.697 
-26 1 -6.078 16.378 9.610 
-27 1 9.864 -7.944 9.546 
-28 1 1.818 14.962 0.802 
-29 1 7.646 12.030 8.284 
-30 1 -10.964 -12.808 -7.521 
-31 1 -14.941 -13.848 2.867 
-32 1 14.608 7.279 14.746 
-33 1 -15.323 12.729 -11.010 
-34 1 9.746 7.475 -4.331 
-35 1 -15.316 5.433 -9.228 
-36 1 -13.980 -16.431 5.514 
-37 1 14.132 4.469 -16.202 
-38 1 2.853 15.548 -14.326 
-39 1 15.735 4.380 -12.264 
-40 1 7.269 4.273 -8.794 
-41 1 -11.665 -10.074 -4.357 
-42 1 1.613 -8.731 11.079 
-43 1 2.619 0.002 12.079 
-44 1 -3.697 -14.298 -4.834 
-45 1 -9.356 -15.806 -9.901 
-46 1 12.969 2.841 -10.985 
-47 1 -2.227 -13.084 -8.525 
-48 1 -12.442 13.616 14.211 
-49 1 -6.247 -13.417 5.101 
-50 1 7.561 -2.139 -14.080 
-51 1 5.222 11.177 -5.979 
-52 1 10.716 2.057 -8.502 
-53 1 3.787 -3.752 -8.160 
-54 1 -12.168 13.735 -13.208 
-55 1 -6.212 -13.713 -11.635 
-56 1 2.665 -16.168 8.962 
-57 1 0.671 -2.184 -11.857 
-58 1 -0.553 -0.431 4.849 
-59 1 -1.297 16.480 0.030 
-60 1 -9.150 -11.715 3.776 
-61 1 -7.089 6.673 2.196 
-62 1 -8.464 11.255 -3.744 
-63 1 -3.808 -13.372 -1.215 
-64 1 12.971 -15.571 -15.577 
-65 1 0.466 -10.724 0.437 
-66 1 -3.006 14.155 8.144 
-67 1 5.036 4.954 -4.433 
-68 1 5.360 9.892 0.026 
-69 1 14.253 10.929 13.289 
-70 1 -5.867 -6.673 16.372 
-71 1 -4.967 3.506 -3.541 
-72 1 9.999 -6.194 -3.598 
-73 1 -12.561 -9.668 -7.819 
-74 1 -15.624 -9.605 -3.805 
-75 1 8.200 5.296 6.381 
-76 1 1.969 12.774 -8.115 
-77 1 9.243 10.764 -8.262 
-78 1 -1.670 -0.797 -2.080 
-79 1 3.363 12.016 -15.931 
-80 1 -9.575 -7.347 -5.452 
-81 1 7.218 10.191 -2.786 
-82 1 8.183 11.489 13.632 
-83 1 6.943 8.159 -10.462 
-84 1 3.861 -16.189 14.535 
-85 1 4.146 2.926 -10.235 
-86 1 -13.739 -5.574 3.978 
-87 1 -3.217 3.935 4.408 
-88 1 -10.173 -14.917 6.402 
-89 1 -0.248 -8.252 4.246 
-90 1 5.819 -13.143 -14.207 
-91 1 -8.617 1.180 7.188 
-92 1 7.045 6.482 -6.267 
-93 1 6.182 -13.626 4.445 
-94 1 0.037 -13.401 2.529 
-95 1 -7.425 5.515 -16.296 
-96 1 -1.152 -16.375 -9.106 
-97 1 -16.420 5.300 0.555 
-98 1 -6.726 -15.498 -6.184 
-99 1 -5.650 15.295 -3.535 
-100 1 13.107 -3.226 3.346 
-101 1 10.866 -0.420 -11.164 
-102 1 11.060 6.154 13.370 
-103 1 10.761 -16.192 -12.646 
-104 1 1.265 -11.329 -13.590 
-105 1 -6.875 -12.597 -15.733 
-106 1 -4.791 -9.110 8.938 
-107 1 0.581 -2.594 10.939 
-108 1 -13.557 5.603 4.550 
-109 1 -3.731 -6.479 -1.036 
-110 1 3.377 -1.047 -16.358 
-111 1 -6.367 15.178 -11.331 
-112 1 -10.442 -1.389 10.989 
-113 1 15.365 -8.013 16.052 
-114 1 12.258 -9.159 12.308 
-115 1 -11.675 11.340 -1.909 
-116 1 15.318 -8.728 5.709 
-117 1 -8.610 -15.017 2.743 
-118 1 -12.433 15.057 -2.807 
-119 1 -12.949 3.228 13.277 
-120 1 -2.211 -15.527 7.046 
-121 1 2.409 8.969 13.143 
-122 1 14.343 -12.578 3.964 
-123 1 -10.219 -11.806 -10.788 
-124 1 -9.628 1.376 1.095 
-125 1 -2.615 -9.806 6.367 
-126 1 15.088 -4.248 -4.705 
-127 1 -13.319 0.883 2.205 
-128 1 3.332 -9.232 3.907 
-129 1 -9.141 -1.898 5.595 
-130 1 -0.723 10.612 12.788 
-131 1 -12.546 -9.644 -15.068 
-132 1 -16.440 -12.422 14.787 
-133 1 -13.916 11.561 7.455 
-134 1 -15.932 12.309 -0.611 
-135 1 12.090 11.106 2.518 
-136 1 6.191 -12.730 13.730 
-137 1 -5.105 -3.008 -8.545 
-138 1 12.812 -11.418 15.225 
-139 1 6.317 5.229 3.332 
-140 1 -10.491 15.439 10.382 
-141 1 -8.940 -13.089 -4.344 
-142 1 7.268 13.508 -8.237 
-143 1 7.825 -4.828 -0.917 
-144 1 -8.630 14.855 7.171 
-145 1 -2.958 2.377 0.457 
-146 1 6.766 -1.691 -10.333 
-147 1 6.633 -12.373 8.087 
-148 1 -7.343 0.836 -7.147 
-149 1 -0.706 14.280 -4.819 
-150 1 -0.836 14.701 4.628 
-151 1 -3.640 -14.978 4.141 
-152 1 7.261 -8.050 -14.734 
-153 1 10.148 -10.828 5.910 
-154 1 -4.410 -0.674 5.039 
-155 1 7.721 -8.987 13.687 
-156 1 8.885 14.302 2.210 
-157 1 -3.787 -0.836 14.782 
-158 1 1.896 9.277 -1.126 
-159 1 13.049 -7.628 -6.796 
-160 1 -9.150 -5.168 -14.507 
-161 1 11.172 8.651 -0.703 
-162 1 -13.654 -0.582 6.238 
-163 1 -13.045 9.390 2.968 
-164 1 -11.473 7.451 8.295 
-165 1 8.131 8.853 2.517 
-166 1 -13.999 -10.321 3.936 
-167 1 -6.481 -1.587 10.437 
-168 1 -2.285 -9.728 -6.636 
-169 1 -3.013 12.781 -14.447 
-170 1 4.235 9.228 -8.906 
-171 1 11.032 2.851 16.004 
-172 1 14.117 -0.709 8.490 
-173 1 4.007 7.067 5.955 
-174 1 -3.363 -9.711 -2.379 
-175 1 8.018 15.103 5.153 
-176 1 2.957 -16.244 4.763 
-177 1 13.235 -12.154 9.276 
-178 1 -5.670 14.905 -8.126 
-179 1 -6.459 3.363 2.058 
-180 1 -2.493 8.147 -16.315 
-181 1 14.109 5.916 -8.608 
-182 1 11.272 7.084 -11.492 
-183 1 8.869 -0.664 -6.492 
-184 1 9.479 3.873 -12.961 
-185 1 -12.171 14.187 3.156 
-186 1 0.016 -3.638 -6.442 
-187 1 -13.770 -13.178 -3.622 
-188 1 -5.268 10.750 -2.319 
-189 1 -9.702 10.000 5.163 
-190 1 -5.741 15.992 -16.259 
-191 1 -6.442 11.975 2.022 
-192 1 -15.560 -7.077 -10.647 
-193 1 -2.763 -5.824 7.579 
-194 1 -6.624 1.990 14.548 
-195 1 -15.980 6.687 10.669 
-196 1 -11.329 1.894 9.306 
-197 1 11.738 -15.729 13.752 
-198 1 7.313 -0.039 2.263 
-199 1 -4.956 -10.361 -12.963 
-200 1 -5.143 -12.161 2.218 
diff --git a/illustration/Equation-of-state/lammps_tau4.55/input.lmp b/illustration/Equation-of-state/lammps_tau4.55/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau4.55/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau4.55/pressure.dat b/illustration/Equation-of-state/lammps_tau4.55/pressure.dat
deleted file mode 100644
index 9e3068b..0000000
--- a/illustration/Equation-of-state/lammps_tau4.55/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 258.983
-1000 259.071
-2000 292.12
-3000 277.404
-4000 278.059
-5000 258.574
-6000 269.663
-7000 304.452
-8000 284.444
-9000 279.952
-10000 323.92
-11000 293.243
-12000 305.01
-13000 297.124
-14000 262.954
-15000 266.125
-16000 302.834
-17000 359.466
-18000 258.926
-19000 249.829
-20000 280.743
diff --git a/illustration/Equation-of-state/lammps_tau4.55/variable.lammps b/illustration/Equation-of-state/lammps_tau4.55/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau4.55/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/lammps_tau5.89/Epot.dat b/illustration/Equation-of-state/lammps_tau5.89/Epot.dat
deleted file mode 100644
index 320efc9..0000000
--- a/illustration/Equation-of-state/lammps_tau5.89/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 -51.5106
-1000 -54.8431
-2000 -48.733
-3000 -53.493
-4000 -50.5662
-5000 -48.1685
-6000 -51.0392
-7000 -50.6228
-8000 -51.2008
-9000 -47.6827
-10000 -51.9714
-11000 -47.5482
-12000 -50.0901
-13000 -47.6582
-14000 -47.0602
-15000 -51.7184
-16000 -45.3636
-17000 -41.6262
-18000 -46.1127
-19000 -45.6477
-20000 -52.2005
diff --git a/illustration/Equation-of-state/lammps_tau5.89/PARM.lammps b/illustration/Equation-of-state/lammps_tau5.89/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau5.89/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau5.89/initial.data b/illustration/Equation-of-state/lammps_tau5.89/initial.data
deleted file mode 100644
index d5c82ed..0000000
--- a/illustration/Equation-of-state/lammps_tau5.89/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--17.981 17.981 xlo xhi
--17.981 17.981 ylo yhi
--17.981 17.981 zlo zhi
-
-Atoms
-
-1 1 -11.206 -11.379 4.051 
-2 1 14.369 14.912 9.578 
-3 1 5.441 -15.080 -0.833 
-4 1 -8.897 4.526 11.325 
-5 1 -17.955 -11.863 13.543 
-6 1 -15.712 -2.747 -0.360 
-7 1 -2.261 2.358 -11.254 
-8 1 1.089 7.619 15.229 
-9 1 -11.206 3.095 6.017 
-10 1 -7.357 5.220 5.473 
-11 1 14.697 -6.543 11.929 
-12 1 10.032 -15.666 13.592 
-13 1 6.083 16.393 -8.004 
-14 1 -7.129 -8.460 -5.296 
-15 1 10.228 -12.122 9.104 
-16 1 -9.387 14.626 -0.233 
-17 1 0.071 -1.691 1.238 
-18 1 11.979 15.398 -15.252 
-19 1 -4.473 12.635 2.525 
-20 1 16.806 -11.125 -13.208 
-21 1 -16.643 -6.647 7.701 
-22 1 -4.503 4.976 12.610 
-23 1 16.768 -1.362 -11.072 
-24 1 -14.308 -12.360 1.021 
-25 1 -17.542 -8.143 -7.798 
-26 1 -7.251 16.036 10.557 
-27 1 13.728 -9.710 10.619 
-28 1 1.983 16.941 -0.495 
-29 1 8.669 12.477 7.682 
-30 1 -12.184 -12.257 -9.214 
-31 1 17.801 -14.346 3.466 
-32 1 15.933 8.442 15.393 
-33 1 -15.807 15.163 -11.014 
-34 1 9.509 8.402 -4.650 
-35 1 -16.892 7.732 -9.392 
-36 1 -16.589 17.816 5.356 
-37 1 16.030 5.941 -16.911 
-38 1 3.298 -17.867 -15.473 
-39 1 16.985 5.849 -11.667 
-40 1 8.841 3.170 -9.961 
-41 1 -12.548 -10.619 -5.861 
-42 1 1.275 -10.145 13.077 
-43 1 2.939 -0.294 12.686 
-44 1 -3.472 -16.731 -4.298 
-45 1 -7.743 16.540 -13.827 
-46 1 15.437 2.746 -12.745 
-47 1 -1.808 -13.424 -11.275 
-48 1 -15.563 15.100 14.907 
-49 1 -6.439 -13.458 6.098 
-50 1 8.723 -1.890 -15.005 
-51 1 7.057 11.059 -7.454 
-52 1 12.056 -0.339 -9.449 
-53 1 4.240 -4.185 -8.833 
-54 1 -12.511 14.667 -13.862 
-55 1 -10.277 -16.941 -9.603 
-56 1 2.204 -16.947 10.344 
-57 1 0.540 -2.251 -12.005 
-58 1 -1.494 -4.055 4.913 
-59 1 1.280 14.978 2.301 
-60 1 -7.166 -9.778 4.368 
-61 1 -8.197 6.634 0.766 
-62 1 -8.387 12.707 -2.630 
-63 1 -4.800 -13.406 -3.736 
-64 1 13.679 -17.142 -16.913 
-65 1 1.198 -11.288 0.795 
-66 1 -4.019 15.596 9.201 
-67 1 6.084 6.678 -7.101 
-68 1 7.427 8.527 0.029 
-69 1 15.094 12.275 14.302 
-70 1 -5.810 -7.115 17.782 
-71 1 -5.697 4.463 -4.312 
-72 1 10.137 -6.901 -3.217 
-73 1 -14.869 -9.734 -8.131 
-74 1 -17.368 -10.256 -4.493 
-75 1 9.548 4.608 7.212 
-76 1 1.569 14.634 -9.610 
-77 1 10.195 11.748 -9.173 
-78 1 -2.445 -0.868 -1.851 
-79 1 3.363 14.436 17.327 
-80 1 -9.361 -8.199 -8.802 
-81 1 7.648 11.683 -2.730 
-82 1 9.290 11.765 15.287 
-83 1 7.602 9.009 -10.783 
-84 1 3.872 17.964 16.202 
-85 1 4.223 4.480 -10.473 
-86 1 -15.710 -5.670 4.409 
-87 1 -4.190 4.614 4.023 
-88 1 -11.895 -15.994 7.320 
-89 1 -3.244 -9.828 4.747 
-90 1 6.219 -14.025 -15.760 
-91 1 -8.825 0.534 7.056 
-92 1 10.930 6.216 -7.487 
-93 1 7.918 -15.933 4.053 
-94 1 -0.212 -14.259 2.649 
-95 1 -7.319 5.641 -17.348 
-96 1 -1.909 -17.793 -10.257 
-97 1 16.812 5.985 -0.187 
-98 1 -6.556 -17.863 -5.949 
-99 1 -6.838 -17.970 -2.424 
-100 1 14.150 -3.042 3.557 
-101 1 11.453 1.782 -13.383 
-102 1 10.693 6.888 15.174 
-103 1 11.231 -16.928 -13.846 
-104 1 1.742 -12.381 -14.390 
-105 1 -6.379 -14.717 -15.714 
-106 1 -5.222 -11.577 10.699 
-107 1 0.937 -2.953 11.441 
-108 1 -13.281 6.258 4.983 
-109 1 -3.150 -6.560 -1.167 
-110 1 4.028 -1.120 17.898 
-111 1 -3.800 -16.686 -12.815 
-112 1 -12.219 -0.939 11.849 
-113 1 16.239 -8.181 17.562 
-114 1 11.204 -11.247 15.291 
-115 1 -11.972 11.838 -1.635 
-116 1 17.688 -11.480 5.600 
-117 1 -6.866 -16.026 3.121 
-118 1 -13.238 15.458 -1.281 
-119 1 -14.808 2.940 14.313 
-120 1 -2.984 -16.657 8.602 
-121 1 2.778 10.172 14.235 
-122 1 14.491 -11.558 4.327 
-123 1 -10.207 -12.179 -11.977 
-124 1 -10.712 1.768 -0.470 
-125 1 -2.798 -13.082 5.891 
-126 1 17.410 -4.694 -3.529 
-127 1 -12.860 1.879 2.664 
-128 1 3.717 -9.439 4.751 
-129 1 -9.824 -2.909 7.184 
-130 1 -0.842 10.481 14.052 
-131 1 -13.366 -9.474 -13.872 
-132 1 -16.067 -11.736 -16.613 
-133 1 -17.308 12.981 8.035 
-134 1 -17.477 13.555 0.522 
-135 1 13.477 13.089 3.676 
-136 1 6.030 -14.214 14.760 
-137 1 -7.292 -2.563 -8.077 
-138 1 14.076 -14.460 14.817 
-139 1 6.476 4.460 4.185 
-140 1 -11.498 14.862 10.664 
-141 1 -10.191 -14.671 -5.456 
-142 1 9.164 14.920 -9.622 
-143 1 7.610 -4.755 -1.494 
-144 1 -7.524 16.786 7.045 
-145 1 -3.310 2.603 0.314 
-146 1 7.456 -2.634 -11.428 
-147 1 5.281 -13.970 10.507 
-148 1 -8.814 1.408 -7.576 
-149 1 -1.305 15.245 -6.009 
-150 1 0.917 16.480 5.968 
-151 1 -4.917 -17.372 5.819 
-152 1 7.632 -8.404 -15.292 
-153 1 12.713 -14.210 5.103 
-154 1 -3.312 -1.569 3.056 
-155 1 10.495 -8.064 13.353 
-156 1 9.737 16.824 3.134 
-157 1 -3.639 -1.493 15.168 
-158 1 3.318 10.072 -2.545 
-159 1 15.174 -10.356 -7.669 
-160 1 -9.852 -5.804 -15.531 
-161 1 12.681 10.075 -1.889 
-162 1 -13.426 0.102 7.114 
-163 1 -14.462 10.842 3.644 
-164 1 -12.796 8.227 11.618 
-165 1 11.402 9.955 2.266 
-166 1 -13.942 -10.318 5.908 
-167 1 -6.941 -2.135 12.079 
-168 1 -4.115 -13.033 -8.109 
-169 1 -2.539 13.063 -15.054 
-170 1 4.365 9.865 -9.360 
-171 1 13.752 1.732 -17.720 
-172 1 14.277 -1.816 8.953 
-173 1 5.016 8.696 5.829 
-174 1 -3.409 -10.356 -1.880 
-175 1 7.875 15.511 5.845 
-176 1 2.815 -16.677 3.538 
-177 1 14.820 -14.950 10.461 
-178 1 -6.091 -16.978 -10.011 
-179 1 -7.128 3.250 1.474 
-180 1 -2.114 7.689 -17.726 
-181 1 15.376 5.874 -7.340 
-182 1 12.000 5.998 -11.885 
-183 1 7.911 -0.023 -6.805 
-184 1 11.908 6.658 -16.559 
-185 1 -15.012 15.403 2.788 
-186 1 -0.778 -4.086 -5.989 
-187 1 -15.207 -13.467 -4.921 
-188 1 -5.359 11.179 -1.495 
-189 1 -10.155 11.898 5.361 
-190 1 -5.189 17.355 -17.055 
-191 1 -7.717 10.935 1.766 
-192 1 -17.166 -6.773 -10.641 
-193 1 -1.098 -6.721 7.843 
-194 1 -8.622 4.160 15.730 
-195 1 -17.057 7.423 11.978 
-196 1 -14.594 2.390 9.738 
-197 1 14.480 -11.791 16.749 
-198 1 7.647 -0.378 3.609 
-199 1 -6.128 -11.720 -13.069 
-200 1 -5.079 -13.955 1.194 
diff --git a/illustration/Equation-of-state/lammps_tau5.89/input.lmp b/illustration/Equation-of-state/lammps_tau5.89/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau5.89/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau5.89/pressure.dat b/illustration/Equation-of-state/lammps_tau5.89/pressure.dat
deleted file mode 100644
index ae45f6c..0000000
--- a/illustration/Equation-of-state/lammps_tau5.89/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 189.967
-1000 194.545
-2000 223.613
-3000 167.886
-4000 199.59
-5000 200.779
-6000 172.581
-7000 197.234
-8000 194.439
-9000 222.09
-10000 177.129
-11000 192.541
-12000 188.14
-13000 207.898
-14000 205.857
-15000 178.066
-16000 229.635
-17000 247.609
-18000 195.379
-19000 215.599
-20000 136.818
diff --git a/illustration/Equation-of-state/lammps_tau5.89/variable.lammps b/illustration/Equation-of-state/lammps_tau5.89/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau5.89/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/lammps_tau7.62/Epot.dat b/illustration/Equation-of-state/lammps_tau7.62/Epot.dat
deleted file mode 100644
index 4753127..0000000
--- a/illustration/Equation-of-state/lammps_tau7.62/Epot.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat1
-# TimeStep v_Epot
-0 -38.6304
-1000 -42.8812
-2000 -43.3765
-3000 -42.3626
-4000 -40.9832
-5000 -42.6041
-6000 -37.9886
-7000 -42.6507
-8000 -38.525
-9000 -40.417
-10000 -38.3292
-11000 -36.0102
-12000 -42.7872
-13000 -41.4752
-14000 -40.2143
-15000 -37.9847
-16000 -41.8471
-17000 -38.2668
-18000 -41.096
-19000 -41.227
-20000 -38.2318
diff --git a/illustration/Equation-of-state/lammps_tau7.62/PARM.lammps b/illustration/Equation-of-state/lammps_tau7.62/PARM.lammps
deleted file mode 100644
index 8001a35..0000000
--- a/illustration/Equation-of-state/lammps_tau7.62/PARM.lammps
+++ /dev/null
@@ -1,6 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 39.948
-
-pair_coeff 1 1 0.237987582014826 3.4050149007323767
-
diff --git a/illustration/Equation-of-state/lammps_tau7.62/initial.data b/illustration/Equation-of-state/lammps_tau7.62/initial.data
deleted file mode 100644
index 43215f2..0000000
--- a/illustration/Equation-of-state/lammps_tau7.62/initial.data
+++ /dev/null
@@ -1,211 +0,0 @@
-# LAMMPS data file
-
-200 atoms
-1 atom types
-
--19.592 19.592 xlo xhi
--19.592 19.592 ylo yhi
--19.592 19.592 zlo zhi
-
-Atoms
-
-1 1 -15.421 -12.614 6.132 
-2 1 16.173 17.278 11.919 
-3 1 6.434 -16.771 -0.034 
-4 1 -9.798 4.946 13.089 
-5 1 17.920 -11.332 14.459 
-6 1 -16.878 -3.259 -0.388 
-7 1 -2.511 2.871 -12.353 
-8 1 0.241 7.191 16.135 
-9 1 -12.168 3.771 5.053 
-10 1 -8.522 5.486 6.658 
-11 1 17.583 -6.699 12.627 
-12 1 10.448 -16.488 13.826 
-13 1 6.652 16.831 -9.435 
-14 1 -7.725 -9.117 -7.025 
-15 1 13.015 -12.879 9.341 
-16 1 -10.487 15.474 -0.790 
-17 1 0.160 -2.222 1.020 
-18 1 13.150 17.213 -16.301 
-19 1 -4.233 13.931 1.734 
-20 1 -17.051 -13.399 -12.729 
-21 1 -18.784 -7.453 8.445 
-22 1 -4.810 4.720 12.500 
-23 1 19.091 -1.429 -11.688 
-24 1 -16.102 -13.350 1.762 
-25 1 -18.670 -9.129 -8.677 
-26 1 -6.412 17.454 11.479 
-27 1 12.811 -8.538 13.847 
-28 1 0.572 -19.369 0.627 
-29 1 11.745 13.955 6.922 
-30 1 -14.126 -13.947 -10.186 
-31 1 19.358 -14.706 2.914 
-32 1 17.175 9.739 17.602 
-33 1 -16.705 16.919 -11.888 
-34 1 10.113 8.241 -6.765 
-35 1 -17.677 7.623 -11.707 
-36 1 -18.417 -18.470 4.506 
-37 1 17.351 8.010 -16.216 
-38 1 4.016 19.371 -16.330 
-39 1 18.001 5.066 -12.549 
-40 1 9.209 2.728 -10.924 
-41 1 -13.843 -11.371 -6.840 
-42 1 1.491 -11.531 15.932 
-43 1 3.377 0.264 14.429 
-44 1 -4.443 -16.514 -5.962 
-45 1 -8.402 16.957 -13.851 
-46 1 16.381 3.605 -15.810 
-47 1 -1.930 -13.777 -11.950 
-48 1 -16.215 16.669 16.559 
-49 1 -4.012 -13.714 7.275 
-50 1 11.451 -1.501 -16.052 
-51 1 7.492 11.116 -7.013 
-52 1 13.379 2.827 -11.965 
-53 1 3.996 -5.248 -8.954 
-54 1 -13.388 15.217 -15.294 
-55 1 -11.261 -18.081 -13.192 
-56 1 3.060 19.338 9.626 
-57 1 -0.167 -2.806 -11.266 
-58 1 -1.020 -5.180 3.866 
-59 1 1.558 16.097 1.853 
-60 1 -8.279 -12.620 6.202 
-61 1 -9.063 7.914 0.971 
-62 1 -8.535 14.720 -3.113 
-63 1 -1.602 -16.702 -3.195 
-64 1 15.814 -18.898 -19.532 
-65 1 1.093 -12.754 0.167 
-66 1 -5.465 -19.141 9.544 
-67 1 7.327 5.787 -8.680 
-68 1 9.716 14.046 -1.467 
-69 1 16.126 13.706 14.817 
-70 1 -6.746 -8.430 -19.567 
-71 1 -5.902 4.564 -3.865 
-72 1 10.337 -7.248 -3.418 
-73 1 -16.471 -11.512 -8.984 
-74 1 -19.432 -11.259 -5.137 
-75 1 10.231 4.552 8.032 
-76 1 1.604 16.426 -10.577 
-77 1 13.110 13.639 -9.902 
-78 1 -1.697 -1.030 -2.474 
-79 1 4.526 13.914 -19.398 
-80 1 -10.538 -8.417 -10.066 
-81 1 8.869 10.850 -1.795 
-82 1 10.933 12.735 15.777 
-83 1 7.833 11.195 -11.317 
-84 1 4.628 -18.927 18.581 
-85 1 3.342 5.063 -11.827 
-86 1 -16.841 -5.252 4.946 
-87 1 -4.036 5.322 3.080 
-88 1 -11.792 -17.668 9.105 
-89 1 -4.772 -10.900 5.253 
-90 1 6.879 -15.745 -15.965 
-91 1 -10.714 1.203 7.486 
-92 1 12.068 5.998 -9.309 
-93 1 8.158 -18.406 5.311 
-94 1 -0.226 -13.548 3.122 
-95 1 -7.334 5.977 -18.438 
-96 1 -2.996 18.792 -10.873 
-97 1 17.864 7.222 -0.161 
-98 1 -7.127 -18.769 -7.106 
-99 1 -6.295 -17.022 -2.514 
-100 1 15.467 -2.031 4.355 
-101 1 10.902 2.612 -14.965 
-102 1 11.838 7.118 15.081 
-103 1 11.640 -18.927 -13.772 
-104 1 2.771 -13.016 -16.316 
-105 1 -9.371 -17.414 -18.271 
-106 1 -4.481 -11.725 12.097 
-107 1 1.524 -2.531 13.165 
-108 1 -15.756 6.356 5.604 
-109 1 -3.872 -8.329 -1.286 
-110 1 4.678 -1.262 -19.559 
-111 1 -4.903 -19.573 -13.829 
-112 1 -12.732 -2.116 12.835 
-113 1 17.187 -8.842 18.921 
-114 1 13.969 -13.205 13.976 
-115 1 -13.565 13.137 -2.861 
-116 1 18.222 -12.642 6.602 
-117 1 -8.016 -17.596 4.739 
-118 1 -14.387 15.189 -0.444 
-119 1 -15.074 4.407 15.326 
-120 1 -2.284 -18.322 8.983 
-121 1 2.968 11.119 16.077 
-122 1 16.373 -15.658 5.725 
-123 1 -10.953 -14.465 -12.141 
-124 1 -13.325 5.061 1.481 
-125 1 -2.511 -15.382 4.871 
-126 1 19.344 -5.216 -3.681 
-127 1 -11.485 -0.452 2.661 
-128 1 4.801 -10.493 4.119 
-129 1 -11.554 -4.073 8.159 
-130 1 0.030 13.024 16.290 
-131 1 -13.062 -10.509 -11.860 
-132 1 -18.757 -11.099 -18.776 
-133 1 -17.939 14.356 9.715 
-134 1 19.299 14.008 -0.026 
-135 1 14.274 14.080 3.099 
-136 1 6.617 -15.439 15.694 
-137 1 -7.405 -2.752 -10.109 
-138 1 14.300 -16.240 16.754 
-139 1 7.245 4.158 4.429 
-140 1 -11.712 15.711 12.057 
-141 1 -11.688 -15.726 -6.377 
-142 1 10.621 16.034 -10.528 
-143 1 7.736 -5.228 -1.801 
-144 1 -7.866 18.358 7.832 
-145 1 -4.545 1.982 -0.006 
-146 1 8.045 -3.342 -13.288 
-147 1 8.881 -13.226 10.689 
-148 1 -9.705 1.041 -8.418 
-149 1 -1.293 16.479 -5.448 
-150 1 1.596 18.379 5.595 
-151 1 -5.159 -17.188 6.236 
-152 1 6.410 -9.882 -16.545 
-153 1 11.993 -15.451 6.162 
-154 1 -3.866 -1.456 3.741 
-155 1 10.642 -11.783 17.219 
-156 1 8.759 17.794 3.447 
-157 1 -4.785 -2.754 16.305 
-158 1 4.868 12.157 -1.915 
-159 1 16.441 -9.695 -8.469 
-160 1 -10.765 -5.233 -16.387 
-161 1 13.832 11.315 -3.135 
-162 1 -15.348 1.494 7.939 
-163 1 -13.986 11.941 2.580 
-164 1 -13.998 8.846 11.128 
-165 1 9.658 11.840 1.988 
-166 1 -16.429 -8.877 4.273 
-167 1 -7.681 -2.251 13.460 
-168 1 -4.188 -15.069 -9.999 
-169 1 -3.927 14.675 -15.937 
-170 1 5.375 12.536 -9.322 
-171 1 15.201 1.807 -18.559 
-172 1 14.520 -2.528 9.170 
-173 1 6.226 9.393 6.299 
-174 1 -4.318 -11.726 -3.084 
-175 1 9.500 16.355 6.198 
-176 1 4.126 -18.169 4.406 
-177 1 16.728 -15.648 11.663 
-178 1 -7.242 -19.479 -11.159 
-179 1 -8.143 4.167 3.553 
-180 1 -2.160 9.796 -19.057 
-181 1 16.452 6.103 -9.079 
-182 1 13.032 8.524 -14.109 
-183 1 9.858 -0.173 -8.251 
-184 1 10.376 6.536 -15.309 
-185 1 -17.214 17.633 3.281 
-186 1 -0.671 -4.504 -6.259 
-187 1 -16.629 -13.906 -5.323 
-188 1 -6.957 11.842 -1.366 
-189 1 -11.274 13.547 5.247 
-190 1 -6.915 18.427 -17.957 
-191 1 -6.921 10.974 2.831 
-192 1 -18.395 -7.812 -11.673 
-193 1 -0.722 -7.188 9.232 
-194 1 -8.436 3.519 18.129 
-195 1 -19.438 8.668 13.007 
-196 1 -14.338 1.738 11.520 
-197 1 16.390 -13.526 17.212 
-198 1 8.141 -0.904 3.034 
-199 1 -6.978 -12.999 -14.466 
-200 1 -5.051 -15.281 1.156 
diff --git a/illustration/Equation-of-state/lammps_tau7.62/input.lmp b/illustration/Equation-of-state/lammps_tau7.62/input.lmp
deleted file mode 100644
index 44f7ad7..0000000
--- a/illustration/Equation-of-state/lammps_tau7.62/input.lmp
+++ /dev/null
@@ -1,42 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-units real
-dimension 3
-atom_style atomic
-pair_style lj/cut ${cut_off}
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every ${neighbor}
-
-velocity all create ${temp} 4928459
-fix mymc all gcmc 1 0 1 1 29494 ${temp} -0.5 ${displace_mc}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} dump.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file density.dat
-
-run ${maximum_steps}
diff --git a/illustration/Equation-of-state/lammps_tau7.62/pressure.dat b/illustration/Equation-of-state/lammps_tau7.62/pressure.dat
deleted file mode 100644
index f696364..0000000
--- a/illustration/Equation-of-state/lammps_tau7.62/pressure.dat
+++ /dev/null
@@ -1,23 +0,0 @@
-# Time-averaged data for fix myat6
-# TimeStep v_pressure
-0 167.23
-1000 152.369
-2000 147.142
-3000 154.514
-4000 161.693
-5000 146.838
-6000 162.123
-7000 125.168
-8000 155.301
-9000 133.636
-10000 170.152
-11000 173.394
-12000 133.441
-13000 154.758
-14000 144.279
-15000 160.186
-16000 134.903
-17000 158.447
-18000 140.221
-19000 144
-20000 157.959
diff --git a/illustration/Equation-of-state/lammps_tau7.62/variable.lammps b/illustration/Equation-of-state/lammps_tau7.62/variable.lammps
deleted file mode 100644
index 9dbced8..0000000
--- a/illustration/Equation-of-state/lammps_tau7.62/variable.lammps
+++ /dev/null
@@ -1,10 +0,0 @@
-# LAMMPS variable file 
-
-variable neighbor equal 50
-variable thermo equal 1000
-variable dump equal 1000
-variable cut_off equal 8.512537251830942
-variable displace_mc equal 0.6810029801464753
-variable maximum_steps equal 20000
-variable temp equal 328.15
-
diff --git a/illustration/Equation-of-state/literature-data/excess-energy.png b/illustration/Equation-of-state/literature-data/excess-energy.png
deleted file mode 100644
index 30030e3..0000000
Binary files a/illustration/Equation-of-state/literature-data/excess-energy.png and /dev/null differ
diff --git a/illustration/Equation-of-state/literature-data/pv-nrt.png b/illustration/Equation-of-state/literature-data/pv-nrt.png
deleted file mode 100644
index 1e32e16..0000000
Binary files a/illustration/Equation-of-state/literature-data/pv-nrt.png and /dev/null differ
diff --git a/illustration/Equation-of-state/outputs_tau0.75/Epot.dat b/illustration/Equation-of-state/outputs_tau0.75/Epot.dat
deleted file mode 100644
index f73bdf6..0000000
--- a/illustration/Equation-of-state/outputs_tau0.75/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -11.347 
-1000 56.304 
-2000 87.738 
-3000 102.595 
-4000 108.118 
-5000 116.078 
-6000 114.447 
-7000 120.231 
-8000 110.998 
-9000 105.135 
-10000 97.336 
-11000 109.455 
-12000 125.138 
-13000 122.890 
-14000 112.538 
-15000 98.695 
-16000 108.985 
-17000 126.378 
-18000 147.055 
-19000 117.497 
-20000 125.119 
diff --git a/illustration/Equation-of-state/outputs_tau0.75/pressure.dat b/illustration/Equation-of-state/outputs_tau0.75/pressure.dat
deleted file mode 100644
index 1a21348..0000000
--- a/illustration/Equation-of-state/outputs_tau0.75/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 30592.707 
-1000 34143.012 
-2000 35802.062 
-3000 36574.989 
-4000 36868.989 
-5000 37264.267 
-6000 37157.673 
-7000 37420.811 
-8000 36963.542 
-9000 36683.269 
-10000 36281.089 
-11000 36912.517 
-12000 37702.108 
-13000 37572.211 
-14000 37025.843 
-15000 36291.860 
-16000 36800.997 
-17000 37739.428 
-18000 38785.370 
-19000 37262.805 
-20000 37726.371 
diff --git a/illustration/Equation-of-state/outputs_tau0.97/Epot.dat b/illustration/Equation-of-state/outputs_tau0.97/Epot.dat
deleted file mode 100644
index 12d9e18..0000000
--- a/illustration/Equation-of-state/outputs_tau0.97/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -298.922 
-1000 -213.298 
-2000 -178.755 
-3000 -180.142 
-4000 -169.811 
-5000 -162.372 
-6000 -165.959 
-7000 -153.126 
-8000 -166.303 
-9000 -169.558 
-10000 -156.051 
-11000 -157.261 
-12000 -158.473 
-13000 -160.370 
-14000 -172.317 
-15000 -178.548 
-16000 -169.023 
-17000 -170.959 
-18000 -170.331 
-19000 -168.365 
-20000 -164.937 
diff --git a/illustration/Equation-of-state/outputs_tau0.97/pressure.dat b/illustration/Equation-of-state/outputs_tau0.97/pressure.dat
deleted file mode 100644
index 5623251..0000000
--- a/illustration/Equation-of-state/outputs_tau0.97/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 4174.921 
-1000 8015.293 
-2000 9617.876 
-3000 9490.513 
-4000 9908.923 
-5000 10285.751 
-6000 10080.407 
-7000 10588.566 
-8000 10042.897 
-9000 9850.041 
-10000 10428.247 
-11000 10399.755 
-12000 10295.491 
-13000 10267.357 
-14000 9736.549 
-15000 9484.195 
-16000 9889.936 
-17000 9811.134 
-18000 9838.909 
-19000 9916.863 
-20000 10117.616 
diff --git a/illustration/Equation-of-state/outputs_tau1.25/Epot.dat b/illustration/Equation-of-state/outputs_tau1.25/Epot.dat
deleted file mode 100644
index 648efa6..0000000
--- a/illustration/Equation-of-state/outputs_tau1.25/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -285.040 
-1000 -215.544 
-2000 -195.357 
-3000 -201.221 
-4000 -194.619 
-5000 -189.086 
-6000 -189.268 
-7000 -180.977 
-8000 -181.135 
-9000 -191.871 
-10000 -192.686 
-11000 -186.545 
-12000 -188.647 
-13000 -185.250 
-14000 -187.552 
-15000 -177.516 
-16000 -187.811 
-17000 -178.379 
-18000 -193.761 
-19000 -194.960 
-20000 -187.004 
diff --git a/illustration/Equation-of-state/outputs_tau1.25/pressure.dat b/illustration/Equation-of-state/outputs_tau1.25/pressure.dat
deleted file mode 100644
index b5397a0..0000000
--- a/illustration/Equation-of-state/outputs_tau1.25/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -94.319 
-1000 2589.936 
-2000 3320.026 
-3000 3145.603 
-4000 3352.271 
-5000 3560.041 
-6000 3436.576 
-7000 3733.474 
-8000 3717.857 
-9000 3277.037 
-10000 3209.861 
-11000 3451.660 
-12000 3350.942 
-13000 3466.010 
-14000 3378.598 
-15000 3681.751 
-16000 3350.838 
-17000 3659.803 
-18000 3081.899 
-19000 3047.031 
-20000 3344.230 
diff --git a/illustration/Equation-of-state/outputs_tau1.62/Epot.dat b/illustration/Equation-of-state/outputs_tau1.62/Epot.dat
deleted file mode 100644
index 4c7ae0c..0000000
--- a/illustration/Equation-of-state/outputs_tau1.62/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -240.034 
-1000 -179.461 
-2000 -165.591 
-3000 -172.311 
-4000 -165.732 
-5000 -166.820 
-6000 -158.566 
-7000 -151.824 
-8000 -156.452 
-9000 -163.348 
-10000 -159.097 
-11000 -155.317 
-12000 -150.949 
-13000 -153.773 
-14000 -156.843 
-15000 -164.470 
-16000 -167.678 
-17000 -153.078 
-18000 -157.212 
-19000 -152.886 
-20000 -161.681 
diff --git a/illustration/Equation-of-state/outputs_tau1.62/pressure.dat b/illustration/Equation-of-state/outputs_tau1.62/pressure.dat
deleted file mode 100644
index ea64c9b..0000000
--- a/illustration/Equation-of-state/outputs_tau1.62/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -124.417 
-1000 1661.882 
-2000 1935.159 
-3000 1702.488 
-4000 1805.863 
-5000 1767.141 
-6000 1834.398 
-7000 1979.234 
-8000 1830.287 
-9000 1617.358 
-10000 1768.480 
-11000 1774.951 
-12000 1906.148 
-13000 1782.984 
-14000 1676.180 
-15000 1419.323 
-16000 1257.706 
-17000 1671.611 
-18000 1529.505 
-19000 1615.477 
-20000 1366.916 
diff --git a/illustration/Equation-of-state/outputs_tau2.1/Epot.dat b/illustration/Equation-of-state/outputs_tau2.1/Epot.dat
deleted file mode 100644
index b60c343..0000000
--- a/illustration/Equation-of-state/outputs_tau2.1/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -208.863 
-1000 -158.635 
-2000 -135.832 
-3000 -134.988 
-4000 -137.375 
-5000 -131.605 
-6000 -138.863 
-7000 -130.644 
-8000 -132.729 
-9000 -134.787 
-10000 -132.361 
-11000 -129.219 
-12000 -130.226 
-13000 -130.966 
-14000 -127.384 
-15000 -126.879 
-16000 -131.747 
-17000 -129.885 
-18000 -138.555 
-19000 -129.289 
-20000 -129.119 
diff --git a/illustration/Equation-of-state/outputs_tau2.1/pressure.dat b/illustration/Equation-of-state/outputs_tau2.1/pressure.dat
deleted file mode 100644
index 76880df..0000000
--- a/illustration/Equation-of-state/outputs_tau2.1/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 122.015 
-1000 1193.268 
-2000 1544.628 
-3000 1440.260 
-4000 1256.246 
-5000 1364.955 
-6000 1133.486 
-7000 1306.209 
-8000 1138.319 
-9000 1025.128 
-10000 1055.239 
-11000 1112.181 
-12000 1044.880 
-13000 1014.296 
-14000 1071.196 
-15000 1004.749 
-16000 874.632 
-17000 874.264 
-18000 713.497 
-19000 964.317 
-20000 932.414 
diff --git a/illustration/Equation-of-state/outputs_tau2.72/Epot.dat b/illustration/Equation-of-state/outputs_tau2.72/Epot.dat
deleted file mode 100644
index 6691634..0000000
--- a/illustration/Equation-of-state/outputs_tau2.72/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -178.058 
-1000 -131.353 
-2000 -117.797 
-3000 -119.140 
-4000 -112.510 
-5000 -108.457 
-6000 -107.357 
-7000 -102.548 
-8000 -101.910 
-9000 -109.813 
-10000 -102.762 
-11000 -100.442 
-12000 -110.835 
-13000 -110.536 
-14000 -108.844 
-15000 -112.030 
-16000 -111.156 
-17000 -107.473 
-18000 -109.230 
-19000 -103.227 
-20000 -96.124 
diff --git a/illustration/Equation-of-state/outputs_tau2.72/pressure.dat b/illustration/Equation-of-state/outputs_tau2.72/pressure.dat
deleted file mode 100644
index 6e288ed..0000000
--- a/illustration/Equation-of-state/outputs_tau2.72/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 169.799 
-1000 903.381 
-2000 1016.764 
-3000 906.245 
-4000 901.598 
-5000 953.433 
-6000 952.237 
-7000 1001.757 
-8000 921.580 
-9000 732.190 
-10000 826.813 
-11000 820.766 
-12000 646.898 
-13000 641.180 
-14000 628.409 
-15000 549.161 
-16000 530.246 
-17000 590.367 
-18000 531.602 
-19000 637.326 
-20000 706.851 
diff --git a/illustration/Equation-of-state/outputs_tau3.52/Epot.dat b/illustration/Equation-of-state/outputs_tau3.52/Epot.dat
deleted file mode 100644
index 27b6f61..0000000
--- a/illustration/Equation-of-state/outputs_tau3.52/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -152.338 
-1000 -112.968 
-2000 -96.872 
-3000 -99.609 
-4000 -95.994 
-5000 -93.775 
-6000 -86.407 
-7000 -82.520 
-8000 -88.819 
-9000 -95.867 
-10000 -93.753 
-11000 -91.415 
-12000 -85.890 
-13000 -85.282 
-14000 -86.740 
-15000 -83.587 
-16000 -86.423 
-17000 -80.854 
-18000 -87.444 
-19000 -84.636 
-20000 -86.483 
diff --git a/illustration/Equation-of-state/outputs_tau3.52/pressure.dat b/illustration/Equation-of-state/outputs_tau3.52/pressure.dat
deleted file mode 100644
index 74e2286..0000000
--- a/illustration/Equation-of-state/outputs_tau3.52/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 187.610 
-1000 650.322 
-2000 751.668 
-3000 597.715 
-4000 569.684 
-5000 577.299 
-6000 658.896 
-7000 655.649 
-8000 548.942 
-9000 419.353 
-10000 445.974 
-11000 459.483 
-12000 518.273 
-13000 495.497 
-14000 475.547 
-15000 475.689 
-16000 407.039 
-17000 435.049 
-18000 341.826 
-19000 358.580 
-20000 316.282 
diff --git a/illustration/Equation-of-state/outputs_tau4.55/Epot.dat b/illustration/Equation-of-state/outputs_tau4.55/Epot.dat
deleted file mode 100644
index 0290c51..0000000
--- a/illustration/Equation-of-state/outputs_tau4.55/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -128.926 
-1000 -87.958 
-2000 -86.310 
-3000 -84.536 
-4000 -83.193 
-5000 -79.850 
-6000 -78.480 
-7000 -73.219 
-8000 -74.218 
-9000 -78.601 
-10000 -68.131 
-11000 -72.805 
-12000 -71.293 
-13000 -66.350 
-14000 -74.323 
-15000 -70.737 
-16000 -71.307 
-17000 -67.650 
-18000 -68.388 
-19000 -67.113 
-20000 -66.264 
diff --git a/illustration/Equation-of-state/outputs_tau4.55/pressure.dat b/illustration/Equation-of-state/outputs_tau4.55/pressure.dat
deleted file mode 100644
index b3bd230..0000000
--- a/illustration/Equation-of-state/outputs_tau4.55/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 167.602 
-1000 538.480 
-2000 446.426 
-3000 387.650 
-4000 332.085 
-5000 350.723 
-6000 366.763 
-7000 357.741 
-8000 321.841 
-9000 266.222 
-10000 354.172 
-11000 316.174 
-12000 330.409 
-13000 366.812 
-14000 278.997 
-15000 300.457 
-16000 274.914 
-17000 277.317 
-18000 282.140 
-19000 270.674 
-20000 258.930 
diff --git a/illustration/Equation-of-state/outputs_tau5.89/Epot.dat b/illustration/Equation-of-state/outputs_tau5.89/Epot.dat
deleted file mode 100644
index 82227a8..0000000
--- a/illustration/Equation-of-state/outputs_tau5.89/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -109.274 
-1000 -72.888 
-2000 -64.284 
-3000 -65.122 
-4000 -67.966 
-5000 -65.207 
-6000 -59.589 
-7000 -53.986 
-8000 -60.422 
-9000 -64.468 
-10000 -56.223 
-11000 -57.525 
-12000 -48.680 
-13000 -54.975 
-14000 -57.845 
-15000 -56.120 
-16000 -51.925 
-17000 -50.803 
-18000 -51.659 
-19000 -52.761 
-20000 -51.513 
diff --git a/illustration/Equation-of-state/outputs_tau5.89/pressure.dat b/illustration/Equation-of-state/outputs_tau5.89/pressure.dat
deleted file mode 100644
index 6101bc9..0000000
--- a/illustration/Equation-of-state/outputs_tau5.89/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 152.720 
-1000 373.280 
-2000 360.497 
-3000 296.236 
-4000 232.235 
-5000 250.413 
-6000 287.347 
-7000 306.686 
-8000 227.374 
-9000 178.137 
-10000 222.357 
-11000 209.771 
-12000 284.470 
-13000 237.147 
-14000 214.392 
-15000 200.679 
-16000 238.069 
-17000 223.507 
-18000 218.592 
-19000 192.753 
-20000 189.984 
diff --git a/illustration/Equation-of-state/outputs_tau7.62/Epot.dat b/illustration/Equation-of-state/outputs_tau7.62/Epot.dat
deleted file mode 100644
index 56fc4e8..0000000
--- a/illustration/Equation-of-state/outputs_tau7.62/Epot.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 -92.919 
-1000 -60.064 
-2000 -61.413 
-3000 -57.050 
-4000 -58.870 
-5000 -49.704 
-6000 -48.341 
-7000 -45.899 
-8000 -47.944 
-9000 -50.911 
-10000 -43.185 
-11000 -44.825 
-12000 -47.152 
-13000 -44.602 
-14000 -42.426 
-15000 -43.605 
-16000 -39.916 
-17000 -33.102 
-18000 -38.112 
-19000 -36.952 
-20000 -38.639 
diff --git a/illustration/Equation-of-state/outputs_tau7.62/pressure.dat b/illustration/Equation-of-state/outputs_tau7.62/pressure.dat
deleted file mode 100644
index 9e6bfd9..0000000
--- a/illustration/Equation-of-state/outputs_tau7.62/pressure.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-0 122.090 
-1000 274.464 
-2000 213.749 
-3000 203.344 
-4000 159.089 
-5000 221.182 
-6000 224.392 
-7000 216.742 
-8000 177.982 
-9000 153.777 
-10000 190.712 
-11000 174.036 
-12000 158.216 
-13000 166.910 
-14000 167.320 
-15000 157.585 
-16000 183.672 
-17000 218.345 
-18000 187.605 
-19000 185.467 
-20000 167.159 
diff --git a/illustration/Equation-of-state/pv-nrt-dm.png b/illustration/Equation-of-state/pv-nrt-dm.png
deleted file mode 100644
index eb08733..0000000
Binary files a/illustration/Equation-of-state/pv-nrt-dm.png and /dev/null differ
diff --git a/illustration/Equation-of-state/pv-nrt-pyplot.ipynb b/illustration/Equation-of-state/pv-nrt-pyplot.ipynb
deleted file mode 100644
index 00b288a..0000000
--- a/illustration/Equation-of-state/pv-nrt-pyplot.ipynb
+++ /dev/null
@@ -1,193 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "15134151",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")\n",
-    "\n",
-    "import numpy as np\n",
-    "import sys, os, git\n",
-    "from scipy import constants as cst\n",
-    "from pint import UnitRegistry\n",
-    "ureg = UnitRegistry()\n",
-    "ureg = UnitRegistry(autoconvert_offset_to_baseunit = True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "11014d02",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "current_path = os.getcwd()\n",
-    "git_repo = git.Repo(current_path, search_parent_directories=True)\n",
-    "git_path = git_repo.git.rev_parse(\"--show-toplevel\")\n",
-    "path_in_folder = current_path[len(git_path)+1:]\n",
-    "sys.path.append(git_path + \"/pyplot-perso\")\n",
-    "from plttools import PltTools\n",
-    "path_figures = current_path[len(git_path):] + '/'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "Wood1957 = np.loadtxt(\"literature-data/pv-nrt.dat\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "d51e3f62",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "kB = cst.Boltzmann*ureg.J/ureg.kelvin # boltzman constant\n",
-    "Na = cst.Avogadro/ureg.mole # avogadro\n",
-    "R = kB*Na # gas constant\n",
-    "\n",
-    "r_star = 3.822*ureg.angstrom # angstrom\n",
-    "sigma = r_star / 2**(1/6) # angstrom\n",
-    "N_atom = 200 # no units\n",
-    "T = (55 * ureg.degC).to(ureg.degK) # 55°C\n",
-    "volume_star = r_star**3 * Na * 2**(-0.5) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "eb775da8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "jump = 10\n",
-    "N_atom = 200\n",
-    "T = (55 * ureg.degC).to(ureg.degK) # 55°C\n",
-    "pressure_vs_tau = []\n",
-    "for folder in [x[0] for x in os.walk(\"./\")]:\n",
-    "    if \"outputs_tau\" in folder:\n",
-    "        pressure = np.mean(np.loadtxt(folder+\"/pressure.dat\")[:,1][jump:]) # atm\n",
-    "        pressure = (pressure*ureg.atm).to(ureg.pascal)\n",
-    "        tau = np.float32(folder.split(\"./outputs_tau\")[1])\n",
-    "        volume = (volume_star * tau / Na).to(ureg.meter**3)\n",
-    "        pressure_normalized = pressure * volume / (R * T) * Na\n",
-    "        pressure_vs_tau.append([tau, pressure_normalized.magnitude])\n",
-    "pressure_vs_tau = np.array(pressure_vs_tau)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "cd60cbf6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "jump = 10\n",
-    "N_atom = 200\n",
-    "T = (55 * ureg.degC).to(ureg.degK) # 55°C\n",
-    "pressure_vs_tau_lmp = []\n",
-    "for folder in [x[0] for x in os.walk(\"./\")]:\n",
-    "    if \"lammps_tau\" in folder:\n",
-    "        pressure = np.mean(np.loadtxt(folder+\"/pressure.dat\")[:,1][jump:]) # atm\n",
-    "        pressure = (pressure*ureg.atm).to(ureg.pascal)\n",
-    "        tau = np.float32(folder.split(\"./lammps_tau\")[1])\n",
-    "        volume = (volume_star * tau / Na).to(ureg.meter**3)\n",
-    "        pressure_normalized = pressure * volume / (R * T) * Na\n",
-    "        pressure_vs_tau_lmp.append([tau, pressure_normalized.magnitude])\n",
-    "pressure_vs_tau_lmp = np.array(pressure_vs_tau_lmp)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "19f9a92f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1800x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
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",
-      "text/plain": [
-       "<Figure size 1800x800 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "filename = \"pv-nrt\"\n",
-    "for dark_mode in [False, True]:\n",
-    "    myplt = PltTools()\n",
-    "    myplt.prepare_figure(fig_size = (18,8), dark_mode = dark_mode,\n",
-    "                        transparency = True, use_serif=True)\n",
-    "    myplt.add_panel()\n",
-    "    myplt.add_plot(x = Wood1957[:,0], y = Wood1957[:,1], type = \"loglog\",\n",
-    "                   linewidth_data = 3, marker = \"p\", data_color = \"autogray\",\n",
-    "                   markersize = 16, data_label = r'$\\mathrm{Wood1957}$')\n",
-    "    myplt.add_plot(x = pressure_vs_tau_lmp[:,0], y = pressure_vs_tau_lmp[:,1], type = \"loglog\",\n",
-    "                   linewidth_data = 3, marker = \"s\", data_color = 1,\n",
-    "                   markersize = 16, data_label = r'$\\mathrm{LAMMPS}$')\n",
-    "    myplt.add_plot(x = pressure_vs_tau[:,0], y = pressure_vs_tau[:,1], type = \"loglog\",\n",
-    "                   linewidth_data = 3, marker = \"o\", data_color = np.array([0, 0.8, 0.8]),\n",
-    "                   markersize = 16, data_label = r'$\\mathrm{MC~move}$')\n",
-    "    myplt.complete_panel(ylabel = r'$p V / R T$', xlabel = r'$v / v^*$',\n",
-    "                         xpad = 15, legend=True, handlelength_legend=1)\n",
-    "    myplt.set_boundaries(x_boundaries=(0.6, 11), # y_ticks=np.arange(-2., 0.6, 0.5),\n",
-    "                         y_boundaries=(0.3, 130))\n",
-    "    myplt.save_figure(filename = filename, saving_path = './')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "da0c3fde",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3.10.6 64-bit",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.3"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/illustration/Equation-of-state/pv-nrt.png b/illustration/Equation-of-state/pv-nrt.png
deleted file mode 100644
index 1ab1f0c..0000000
Binary files a/illustration/Equation-of-state/pv-nrt.png and /dev/null differ
diff --git a/illustration/Equation-of-state/vmd/avatar-dm.webp b/illustration/Equation-of-state/vmd/avatar-dm.webp
deleted file mode 100644
index 5f44a11..0000000
Binary files a/illustration/Equation-of-state/vmd/avatar-dm.webp and /dev/null differ
diff --git a/illustration/Equation-of-state/vmd/avatar.png b/illustration/Equation-of-state/vmd/avatar.png
deleted file mode 100644
index f96b847..0000000
Binary files a/illustration/Equation-of-state/vmd/avatar.png and /dev/null differ
diff --git a/illustration/Equation-of-state/vmd/avatar.webp b/illustration/Equation-of-state/vmd/avatar.webp
deleted file mode 100644
index 181c871..0000000
Binary files a/illustration/Equation-of-state/vmd/avatar.webp and /dev/null differ
diff --git a/illustration/Equation-of-state/vmd/convert_transparent.sh b/illustration/Equation-of-state/vmd/convert_transparent.sh
deleted file mode 100755
index f5e9cf5..0000000
--- a/illustration/Equation-of-state/vmd/convert_transparent.sh
+++ /dev/null
@@ -1,18 +0,0 @@
-#!/bin/bash
-
-export LC_NUMERIC="en_US.UTF-8"
-set -e
-
-# 1) Generate white background movie
-for file in _light.*.ppm; 
-do 
-	convert $file -transparent white ${file:0:12}.png;
-done
-img2webp -o avatar.webp -q 30 -mixed -d 25 _light*.png
-
-# 2) Generate black background movie
-for file in _dark.*.ppm; 
-do 
-	convert $file -transparent black ${file:0:11}.png;
-done
-img2webp -o avatar-dm.webp -q 30 -mixed -d 25 _dark*.png
diff --git a/illustration/Equation-of-state/vmd/state.vmd b/illustration/Equation-of-state/vmd/state.vmd
deleted file mode 100644
index fcde0ee..0000000
--- a/illustration/Equation-of-state/vmd/state.vmd
+++ /dev/null
@@ -1,549 +0,0 @@
-#!/usr/local/bin/vmd
-# VMD script written by save_state $Revision: 1.48 $
-# VMD version: 1.9.4a57
-set viewplist {}
-set fixedlist {}
-proc vmdrestoremymaterials {} {
-  set mlist { Opaque Transparent BrushedMetal Diffuse Ghost Glass1 Glass2 Glass3 Glossy HardPlastic MetallicPastel Steel Translucent Edgy EdgyShiny EdgyGlass Goodsell AOShiny AOChalky AOEdgy BlownGlass GlassBubble RTChrome }
-  set mymlist [material list]
-  foreach mat $mlist {
-    if { [lsearch $mymlist $mat] == -1 } { 
-      material add $mat
-    }
-  }
-  material change ambient Opaque 0.000000
-  material change diffuse Opaque 0.560000
-  material change specular Opaque 0.120000
-  material change shininess Opaque 0.290000
-  material change mirror Opaque 0.000000
-  material change opacity Opaque 1.000000
-  material change outline Opaque 0.000000
-  material change outlinewidth Opaque 0.000000
-  material change transmode Opaque 0.000000
-  material change ambient Transparent 0.000000
-  material change diffuse Transparent 0.650000
-  material change specular Transparent 0.500000
-  material change shininess Transparent 0.534020
-  material change mirror Transparent 0.000000
-  material change opacity Transparent 0.300000
-  material change outline Transparent 0.000000
-  material change outlinewidth Transparent 0.000000
-  material change transmode Transparent 0.000000
-  material change ambient BrushedMetal 0.080000
-  material change diffuse BrushedMetal 0.390000
-  material change specular BrushedMetal 0.340000
-  material change shininess BrushedMetal 0.150000
-  material change mirror BrushedMetal 0.000000
-  material change opacity BrushedMetal 1.000000
-  material change outline BrushedMetal 0.000000
-  material change outlinewidth BrushedMetal 0.000000
-  material change transmode BrushedMetal 0.000000
-  material change ambient Diffuse 0.000000
-  material change diffuse Diffuse 0.620000
-  material change specular Diffuse 0.000000
-  material change shininess Diffuse 0.530000
-  material change mirror Diffuse 0.000000
-  material change opacity Diffuse 1.000000
-  material change outline Diffuse 0.000000
-  material change outlinewidth Diffuse 0.000000
-  material change transmode Diffuse 0.000000
-  material change ambient Ghost 0.000000
-  material change diffuse Ghost 0.000000
-  material change specular Ghost 1.000000
-  material change shininess Ghost 0.230000
-  material change mirror Ghost 0.000000
-  material change opacity Ghost 0.100000
-  material change outline Ghost 0.000000
-  material change outlinewidth Ghost 0.000000
-  material change transmode Ghost 0.000000
-  material change ambient Glass1 0.000000
-  material change diffuse Glass1 0.500000
-  material change specular Glass1 0.650000
-  material change shininess Glass1 0.530000
-  material change mirror Glass1 0.000000
-  material change opacity Glass1 0.150000
-  material change outline Glass1 0.000000
-  material change outlinewidth Glass1 0.000000
-  material change transmode Glass1 0.000000
-  material change ambient Glass2 0.520000
-  material change diffuse Glass2 0.760000
-  material change specular Glass2 0.220000
-  material change shininess Glass2 0.590000
-  material change mirror Glass2 0.000000
-  material change opacity Glass2 0.680000
-  material change outline Glass2 0.000000
-  material change outlinewidth Glass2 0.000000
-  material change transmode Glass2 0.000000
-  material change ambient Glass3 0.150000
-  material change diffuse Glass3 0.250000
-  material change specular Glass3 0.750000
-  material change shininess Glass3 0.800000
-  material change mirror Glass3 0.000000
-  material change opacity Glass3 0.500000
-  material change outline Glass3 0.000000
-  material change outlinewidth Glass3 0.000000
-  material change transmode Glass3 0.000000
-  material change ambient Glossy 0.000000
-  material change diffuse Glossy 0.650000
-  material change specular Glossy 1.000000
-  material change shininess Glossy 0.880000
-  material change mirror Glossy 0.000000
-  material change opacity Glossy 1.000000
-  material change outline Glossy 0.000000
-  material change outlinewidth Glossy 0.000000
-  material change transmode Glossy 0.000000
-  material change ambient HardPlastic 0.000000
-  material change diffuse HardPlastic 0.560000
-  material change specular HardPlastic 0.280000
-  material change shininess HardPlastic 0.690000
-  material change mirror HardPlastic 0.000000
-  material change opacity HardPlastic 1.000000
-  material change outline HardPlastic 0.000000
-  material change outlinewidth HardPlastic 0.000000
-  material change transmode HardPlastic 0.000000
-  material change ambient MetallicPastel 0.000000
-  material change diffuse MetallicPastel 0.260000
-  material change specular MetallicPastel 0.550000
-  material change shininess MetallicPastel 0.190000
-  material change mirror MetallicPastel 0.000000
-  material change opacity MetallicPastel 1.000000
-  material change outline MetallicPastel 0.000000
-  material change outlinewidth MetallicPastel 0.000000
-  material change transmode MetallicPastel 0.000000
-  material change ambient Steel 0.250000
-  material change diffuse Steel 0.000000
-  material change specular Steel 0.380000
-  material change shininess Steel 0.320000
-  material change mirror Steel 0.000000
-  material change opacity Steel 1.000000
-  material change outline Steel 0.000000
-  material change outlinewidth Steel 0.000000
-  material change transmode Steel 0.000000
-  material change ambient Translucent 0.000000
-  material change diffuse Translucent 0.700000
-  material change specular Translucent 0.600000
-  material change shininess Translucent 0.300000
-  material change mirror Translucent 0.000000
-  material change opacity Translucent 0.800000
-  material change outline Translucent 0.000000
-  material change outlinewidth Translucent 0.000000
-  material change transmode Translucent 0.000000
-  material change ambient Edgy 0.000000
-  material change diffuse Edgy 0.660000
-  material change specular Edgy 0.000000
-  material change shininess Edgy 0.750000
-  material change mirror Edgy 0.000000
-  material change opacity Edgy 1.000000
-  material change outline Edgy 0.620000
-  material change outlinewidth Edgy 0.940000
-  material change transmode Edgy 0.000000
-  material change ambient EdgyShiny 0.000000
-  material change diffuse EdgyShiny 0.660000
-  material change specular EdgyShiny 0.960000
-  material change shininess EdgyShiny 0.750000
-  material change mirror EdgyShiny 0.000000
-  material change opacity EdgyShiny 1.000000
-  material change outline EdgyShiny 0.760000
-  material change outlinewidth EdgyShiny 0.940000
-  material change transmode EdgyShiny 0.000000
-  material change ambient EdgyGlass 0.000000
-  material change diffuse EdgyGlass 0.660000
-  material change specular EdgyGlass 0.500000
-  material change shininess EdgyGlass 0.750000
-  material change mirror EdgyGlass 0.000000
-  material change opacity EdgyGlass 0.620000
-  material change outline EdgyGlass 0.620000
-  material change outlinewidth EdgyGlass 0.940000
-  material change transmode EdgyGlass 0.000000
-  material change ambient Goodsell 0.520000
-  material change diffuse Goodsell 1.000000
-  material change specular Goodsell 0.000000
-  material change shininess Goodsell 0.000000
-  material change mirror Goodsell 0.000000
-  material change opacity Goodsell 1.000000
-  material change outline Goodsell 4.000000
-  material change outlinewidth Goodsell 0.900000
-  material change transmode Goodsell 0.000000
-  material change ambient AOShiny 0.000000
-  material change diffuse AOShiny 0.850000
-  material change specular AOShiny 0.200000
-  material change shininess AOShiny 0.530000
-  material change mirror AOShiny 0.000000
-  material change opacity AOShiny 1.000000
-  material change outline AOShiny 0.000000
-  material change outlinewidth AOShiny 0.000000
-  material change transmode AOShiny 0.000000
-  material change ambient AOChalky 0.000000
-  material change diffuse AOChalky 0.850000
-  material change specular AOChalky 0.000000
-  material change shininess AOChalky 0.530000
-  material change mirror AOChalky 0.000000
-  material change opacity AOChalky 1.000000
-  material change outline AOChalky 0.000000
-  material change outlinewidth AOChalky 0.000000
-  material change transmode AOChalky 0.000000
-  material change ambient AOEdgy 0.000000
-  material change diffuse AOEdgy 0.900000
-  material change specular AOEdgy 0.200000
-  material change shininess AOEdgy 0.530000
-  material change mirror AOEdgy 0.000000
-  material change opacity AOEdgy 1.000000
-  material change outline AOEdgy 0.620000
-  material change outlinewidth AOEdgy 0.930000
-  material change transmode AOEdgy 0.000000
-  material change ambient BlownGlass 0.040000
-  material change diffuse BlownGlass 0.340000
-  material change specular BlownGlass 1.000000
-  material change shininess BlownGlass 1.000000
-  material change mirror BlownGlass 0.000000
-  material change opacity BlownGlass 0.100000
-  material change outline BlownGlass 0.000000
-  material change outlinewidth BlownGlass 0.000000
-  material change transmode BlownGlass 1.000000
-  material change ambient GlassBubble 0.250000
-  material change diffuse GlassBubble 0.340000
-  material change specular GlassBubble 1.000000
-  material change shininess GlassBubble 1.000000
-  material change mirror GlassBubble 0.000000
-  material change opacity GlassBubble 0.040000
-  material change outline GlassBubble 0.000000
-  material change outlinewidth GlassBubble 0.000000
-  material change transmode GlassBubble 1.000000
-  material change ambient RTChrome 0.000000
-  material change diffuse RTChrome 0.650000
-  material change specular RTChrome 0.500000
-  material change shininess RTChrome 0.530000
-  material change mirror RTChrome 0.700000
-  material change opacity RTChrome 1.000000
-  material change outline RTChrome 0.000000
-  material change outlinewidth RTChrome 0.000000
-  material change transmode RTChrome 0.000000
-}
-vmdrestoremymaterials
-# Atom selection macros
-atomselect macro at {resname ADE A THY T}
-atomselect macro acidic {resname ASP GLU}
-atomselect macro cyclic {resname HIS PHE PRO TRP TYR}
-atomselect macro acyclic {protein and not cyclic}
-atomselect macro aliphatic {resname ALA GLY ILE LEU VAL}
-atomselect macro alpha {protein and name CA}
-atomselect macro amino protein
-atomselect macro aromatic {resname HIS PHE TRP TYR}
-atomselect macro basic {resname ARG HIS LYS HSP}
-atomselect macro bonded {numbonds > 0}
-atomselect macro buried {resname ALA LEU VAL ILE PHE CYS MET TRP}
-atomselect macro cg {resname CYT C GUA G}
-atomselect macro charged {basic or acidic}
-atomselect macro hetero {not (protein or nucleic)}
-atomselect macro hydrophobic {resname ALA LEU VAL ILE PRO PHE MET TRP}
-atomselect macro small {resname ALA GLY SER}
-atomselect macro medium {resname VAL THR ASP ASN PRO CYS ASX PCA HYP}
-atomselect macro large {protein and not (small or medium)}
-atomselect macro neutral {resname VAL PHE GLN TYR HIS CYS MET TRP ASX GLX PCA HYP}
-atomselect macro polar {protein and not hydrophobic}
-atomselect macro purine {resname ADE A GUA G}
-atomselect macro pyrimidine {resname CYT C THY T URA U}
-atomselect macro surface {protein and not buried}
-atomselect macro lipid {resname DLPE DMPC DPPC GPC LPPC PALM PC PGCL POPC POPE}
-atomselect macro lipids lipid
-atomselect macro ion {resname AL BA CA CAL CD CES CLA CL CO CS CU CU1 CUA HG IN IOD K LIT MG MN3 MO3 MO4 MO5 MO6 NA NAW OC7 PB POT PT RB SOD TB TL WO4 YB ZN ZN1 ZN2}
-atomselect macro ions ion
-atomselect macro sugar {resname AGLC}
-atomselect macro solvent {not (protein or sugar or nucleic or lipid)}
-atomselect macro glycan {resname NAG BGLN FUC AFUC MAN AMAN BMA BMAN}
-atomselect macro carbon {name "C.*" and not ion}
-atomselect macro hydrogen {name "[0-9]?H.*"}
-atomselect macro nitrogen {name "N.*"}
-atomselect macro oxygen {name "O.*"}
-atomselect macro sulfur {name "S.*" and not ion}
-atomselect macro noh {not hydrogen}
-atomselect macro heme {resname HEM HEME}
-atomselect macro conformationall {altloc ""}
-atomselect macro conformationA {altloc "" or altloc "A"}
-atomselect macro conformationB {altloc "" or altloc "B"}
-atomselect macro conformationC {altloc "" or altloc "C"}
-atomselect macro conformationD {altloc "" or altloc "D"}
-atomselect macro conformationE {altloc "" or altloc "E"}
-atomselect macro conformationF {altloc "" or altloc "F"}
-atomselect macro drude {type DRUD or type LP}
-atomselect macro unparametrized beta<1
-atomselect macro addedmolefacture {occupancy 0.8}
-atomselect macro qwikmd_protein {(not name QWIKMDDELETE and protein)}
-atomselect macro qwikmd_nucleic {(not name QWIKMDDELETE and nucleic)}
-atomselect macro qwikmd_glycan {(not name QWIKMDDELETE and glycan)}
-atomselect macro qwikmd_lipid {(not name QWIKMDDELETE and lipid)}
-atomselect macro qwikmd_hetero {(not name QWIKMDDELETE and hetero and not qwikmd_protein and not qwikmd_lipid and not qwikmd_nucleic and not qwikmd_glycan and not water)}
-# Display settings
-display eyesep       0.065000
-display focallength  2.000000
-display height       1.000000
-display distance     -2.000000
-display projection   Orthographic
-display nearclip set 0.500000
-display farclip  set 10.000000
-display depthcue   off
-display cuestart   0.500000
-display cueend     10.000000
-display cuestart   0.500000
-display cueend     10.000000
-display cuedensity 0.320000
-display cuemode    Exp2
-display shadows off
-display ambientocclusion off
-display aoambient 0.800000
-display aodirect 0.300000
-display dof off
-display dof_fnumber 64.000000
-display dof_focaldist 0.700000
-mol new dump.mc.lammpstrj type lammpstrj first 0 last -1 step 1 filebonds 1 autobonds 1 waitfor all
-mol delrep 0 top
-mol representation VDW 1.100000 42.000000
-mol color Name
-mol selection {x > -10 and x < 10 and y > -10 and y < 10 and z > -10 and z < 10}
-mol material Opaque
-mol addrep top
-mol selupdate 0 top 0
-mol colupdate 0 top 0
-mol scaleminmax top 0 0.000000 0.000000
-mol smoothrep top 0 0
-mol drawframes top 0 {now}
-mol clipplane center 0 0 top {0.0 0.0 0.0}
-mol clipplane color  0 0 top {0.5 0.5 0.5 }
-mol clipplane normal 0 0 top {0.0 0.0 1.0}
-mol clipplane status 0 0 top {0}
-mol clipplane center 1 0 top {0.0 0.0 0.0}
-mol clipplane color  1 0 top {0.5 0.5 0.5 }
-mol clipplane normal 1 0 top {0.0 0.0 1.0}
-mol clipplane status 1 0 top {0}
-mol clipplane center 2 0 top {0.0 0.0 0.0}
-mol clipplane color  2 0 top {0.5 0.5 0.5 }
-mol clipplane normal 2 0 top {0.0 0.0 1.0}
-mol clipplane status 2 0 top {0}
-mol clipplane center 3 0 top {0.0 0.0 0.0}
-mol clipplane color  3 0 top {0.5 0.5 0.5 }
-mol clipplane normal 3 0 top {0.0 0.0 1.0}
-mol clipplane status 3 0 top {0}
-mol clipplane center 4 0 top {0.0 0.0 0.0}
-mol clipplane color  4 0 top {0.5 0.5 0.5 }
-mol clipplane normal 4 0 top {0.0 0.0 1.0}
-mol clipplane status 4 0 top {0}
-mol clipplane center 5 0 top {0.0 0.0 0.0}
-mol clipplane color  5 0 top {0.5 0.5 0.5 }
-mol clipplane normal 5 0 top {0.0 0.0 1.0}
-mol clipplane status 5 0 top {0}
-mol rename top dump.mc.lammpstrj
-set viewpoints([molinfo top]) {{{1 0 0 0.110355} {0 1 0 0.130033} {0 0 1 -0.0775325} {0 0 0 1}} {{1 0 0 0} {0 1 0 0} {0 0 1 0} {0 0 0 1}} {{0.0199378 0 0 0} {0 0.0199378 0 0} {0 0 0.0199378 0} {0 0 0 1}} {{1 0 0 0} {0 1 0 0} {0 0 1 0} {0 0 0 1}}}
-lappend viewplist [molinfo top]
-set topmol [molinfo top]
-# done with molecule 1
-foreach v $viewplist {
-  molinfo $v set {center_matrix rotate_matrix scale_matrix global_matrix} $viewpoints($v)
-}
-foreach v $fixedlist {
-  molinfo $v set fixed 1
-}
-unset viewplist
-unset fixedlist
-mol top $topmol
-unset topmol
-proc vmdrestoremycolors {} {
-color scale colors RWB {1.0 0.0 0.0} {1.0 1.0 1.0} {0.0 0.0 1.0}
-color scale colors BWR {0.0 0.0 1.0} {1.0 1.0 1.0} {1.0 0.0 0.0}
-color scale colors RGryB {1.0 0.0 0.0} {0.5 0.5 0.5} {0.0 0.0 1.0}
-color scale colors BGryR {0.0 0.0 1.0} {0.5 0.5 0.5} {1.0 0.0 0.0}
-color scale colors RGB {1.0 0.0 0.0} {0.0 1.0 0.0} {0.0 0.0 1.0}
-color scale colors BGR {0.0 0.0 1.0} {0.0 1.0 0.0} {1.0 0.0 0.0}
-color scale colors RWG {1.0 0.0 0.0} {1.0 1.0 1.0} {0.0 1.0 0.0}
-color scale colors GWR {0.0 1.0 0.0} {1.0 1.0 1.0} {1.0 0.0 0.0}
-color scale colors GWB {0.0 1.0 0.0} {1.0 1.0 1.0} {0.0 0.0 1.0}
-color scale colors BWG {0.0 0.0 1.0} {1.0 1.0 1.0} {0.0 1.0 0.0}
-color scale colors BlkW {0.0 0.0 0.0} {0.5 0.5 0.5} {1.0 1.0 1.0}
-color scale colors WBlk {1.0 1.0 1.0} {0.5 0.5 0.5} {0.0 0.0 0.0}
-color scale colors cividis {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors viridis {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors magma {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors plasma {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors inferno {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L3 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L8 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L9 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L16 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L17 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L18 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L19 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L20 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_C2 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_C4 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_C6 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_C7 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_I1 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_I2 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_I3 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_D11 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_D12 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors turbo {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_R2 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-  color scale method RWB
-  set colorcmds {
-    {color Display {BackgroundTop} black}
-    {color Display {BackgroundBot} blue2}
-    {color Display {FPS} white}
-    {color Name {LPA} green}
-    {color Name {LPB} green}
-    {color Name {1} pink}
-    {color Type {LP} green}
-    {color Type {DRUD} pink}
-    {color Type {1} pink}
-    {color Element {X} cyan}
-    {color Element {Ac} ochre}
-    {color Element {Ag} ochre}
-    {color Element {Al} ochre}
-    {color Element {Am} ochre}
-    {color Element {Ar} ochre}
-    {color Element {As} ochre}
-    {color Element {At} ochre}
-    {color Element {Au} ochre}
-    {color Element {B} ochre}
-    {color Element {Ba} ochre}
-    {color Element {Be} ochre}
-    {color Element {Bh} ochre}
-    {color Element {Bi} ochre}
-    {color Element {Bk} ochre}
-    {color Element {Br} ochre}
-    {color Element {Ca} ochre}
-    {color Element {Cd} ochre}
-    {color Element {Ce} ochre}
-    {color Element {Cf} ochre}
-    {color Element {Cl} ochre}
-    {color Element {Cm} ochre}
-    {color Element {Co} ochre}
-    {color Element {Cr} ochre}
-    {color Element {Cs} ochre}
-    {color Element {Cu} ochre}
-    {color Element {Db} ochre}
-    {color Element {Ds} ochre}
-    {color Element {Dy} ochre}
-    {color Element {Er} ochre}
-    {color Element {Es} ochre}
-    {color Element {Eu} ochre}
-    {color Element {F} ochre}
-    {color Element {Fe} ochre}
-    {color Element {Fm} ochre}
-    {color Element {Fr} ochre}
-    {color Element {Ga} ochre}
-    {color Element {Gd} ochre}
-    {color Element {Ge} ochre}
-    {color Element {He} ochre}
-    {color Element {Hf} ochre}
-    {color Element {Hg} ochre}
-    {color Element {Ho} ochre}
-    {color Element {Hs} ochre}
-    {color Element {I} ochre}
-    {color Element {In} ochre}
-    {color Element {Ir} ochre}
-    {color Element {K} ochre}
-    {color Element {Kr} ochre}
-    {color Element {La} ochre}
-    {color Element {Li} ochre}
-    {color Element {Lr} ochre}
-    {color Element {Lu} ochre}
-    {color Element {Md} ochre}
-    {color Element {Mg} ochre}
-    {color Element {Mn} ochre}
-    {color Element {Mo} ochre}
-    {color Element {Mt} ochre}
-    {color Element {Na} ochre}
-    {color Element {Nb} ochre}
-    {color Element {Nd} ochre}
-    {color Element {Ne} ochre}
-    {color Element {Ni} ochre}
-    {color Element {No} ochre}
-    {color Element {Np} ochre}
-    {color Element {Os} ochre}
-    {color Element {Pa} ochre}
-    {color Element {Pb} ochre}
-    {color Element {Pd} ochre}
-    {color Element {Pm} ochre}
-    {color Element {Po} ochre}
-    {color Element {Pr} ochre}
-    {color Element {Pt} ochre}
-    {color Element {Pu} ochre}
-    {color Element {Ra} ochre}
-    {color Element {Rb} ochre}
-    {color Element {Re} ochre}
-    {color Element {Rf} ochre}
-    {color Element {Rg} ochre}
-    {color Element {Rh} ochre}
-    {color Element {Rn} ochre}
-    {color Element {Ru} ochre}
-    {color Element {Sb} ochre}
-    {color Element {Sc} ochre}
-    {color Element {Se} ochre}
-    {color Element {Sg} ochre}
-    {color Element {Si} ochre}
-    {color Element {Sm} ochre}
-    {color Element {Sn} ochre}
-    {color Element {Sr} ochre}
-    {color Element {Ta} ochre}
-    {color Element {Tb} ochre}
-    {color Element {Tc} ochre}
-    {color Element {Te} ochre}
-    {color Element {Th} ochre}
-    {color Element {Ti} ochre}
-    {color Element {Tl} ochre}
-    {color Element {Tm} ochre}
-    {color Element {U} ochre}
-    {color Element {V} ochre}
-    {color Element {W} ochre}
-    {color Element {Xe} ochre}
-    {color Element {Y} ochre}
-    {color Element {Yb} ochre}
-    {color Element {Zr} ochre}
-    {color Resname {UNK} silver}
-    {color Chain {X} blue}
-    {color Segname {} blue}
-    {color Conformation {all} blue}
-    {color Molecule {0} blue}
-    {color Molecule {1} red}
-    {color Molecule {dump.mc.lammpstrj} red}
-    {color Structure {3_10_Helix} blue}
-    {color Surface {Grasp} gray}
-    {color Labels {Springs} orange}
-    {color Stage {Even} gray}
-    {color Stage {Odd} silver}
-  }
-  foreach colcmd $colorcmds {
-    set val [catch {eval $colcmd}]
-  }
-  color change rgb 0 0.0 0.0 1.0
-  color change rgb 2 0.3499999940395355 0.3499999940395355 0.3499999940395355
-  color change rgb 3 1.0 0.5 0.0
-  color change rgb 4 1.0 1.0 0.0
-  color change rgb 5 0.5 0.5 0.20000000298023224
-  color change rgb 6 0.6000000238418579 0.6000000238418579 0.6000000238418579
-  color change rgb 7 0.0 1.0 0.0
-  color change rgb 9 0.0 1.100000023841858 1.100000023841858
-  color change rgb 11 0.6499999761581421 0.0 0.6499999761581421
-  color change rgb 12 0.5 0.8999999761581421 0.4000000059604645
-  color change rgb 13 0.8999999761581421 0.4000000059604645 0.699999988079071
-  color change rgb 14 0.5 0.30000001192092896 0.0
-  color change rgb 15 0.5 0.5 0.75
-  color change rgb 17 0.8799999952316284 0.9700000286102295 0.019999999552965164
-  color change rgb 18 0.550000011920929 0.8999999761581421 0.019999999552965164
-  color change rgb 19 0.0 0.8999999761581421 0.03999999910593033
-  color change rgb 20 0.0 0.8999999761581421 0.5
-  color change rgb 21 0.0 0.8799999952316284 1.0
-  color change rgb 22 0.0 0.7599999904632568 1.0
-  color change rgb 23 0.019999999552965164 0.3799999952316284 0.6700000166893005
-  color change rgb 24 0.009999999776482582 0.03999999910593033 0.9300000071525574
-  color change rgb 25 0.27000001072883606 0.0 0.9800000190734863
-  color change rgb 26 0.44999998807907104 0.0 0.8999999761581421
-  color change rgb 27 0.8999999761581421 0.0 0.8999999761581421
-  color change rgb 28 1.0 0.0 0.6600000262260437
-  color change rgb 29 0.9800000190734863 0.0 0.23000000417232513
-  color change rgb 30 0.8100000023841858 0.0 0.0
-  color change rgb 31 0.8899999856948853 0.3499999940395355 0.0
-  color change rgb 32 0.9599999785423279 0.7200000286102295 0.0
-}
-vmdrestoremycolors
-label textsize 1.0
diff --git a/illustration/Equation-of-state/vmd/vmd.ipynb b/illustration/Equation-of-state/vmd/vmd.ipynb
deleted file mode 100644
index 73786ea..0000000
--- a/illustration/Equation-of-state/vmd/vmd.ipynb
+++ /dev/null
@@ -1,704 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import warnings\n",
-    "warnings.filterwarnings(\"ignore\")\n",
-    "\n",
-    "from scipy import constants as cst\n",
-    "from pint import UnitRegistry\n",
-    "ureg = UnitRegistry()\n",
-    "ureg = UnitRegistry(autoconvert_offset_to_baseunit = True)\n",
-    "import sys\n",
-    "import multiprocessing\n",
-    "import subprocess\n",
-    "import numpy as np\n",
-    "import shutil\n",
-    "import os\n",
-    "\n",
-    "path_to_code = \"../generated-codes/chapter7/\"\n",
-    "sys.path.append(path_to_code)\n",
-    "\n",
-    "from MinimizeEnergy import MinimizeEnergy\n",
-    "from MonteCarlo import MonteCarlo"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "kB = cst.Boltzmann*ureg.J/ureg.kelvin # boltzman constant\n",
-    "Na = cst.Avogadro/ureg.mole # avogadro\n",
-    "R = kB*Na # gas constant"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "tau = 1\n",
-    "epsilon = (119.76*ureg.kelvin*kB*Na).to(ureg.kcal/ureg.mol) # kcal/mol\n",
-    "r_star = 3.822*ureg.angstrom # angstrom\n",
-    "sigma = r_star / 2**(1/6) # angstrom\n",
-    "N_atom = 400 # no units\n",
-    "m_argon = 39.948*ureg.gram/ureg.mol\n",
-    "T = (55 * ureg.degC).to(ureg.degK) # 55°C\n",
-    "volume_star = r_star**3 * Na * 2**(-0.5)\n",
-    "cut_off = sigma*2.5\n",
-    "displace_mc = sigma/5 # angstrom\n",
-    "volume = N_atom*volume_star*tau/Na\n",
-    "box_size = volume**(1/3)\n",
-    "folder = \"./\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "step epot maxF\n",
-      "0 59895733968519.000 9619860237625140.000\n",
-      "10 160614186.280 513067747.593\n",
-      "20 92443.851 27535.614\n",
-      "30 7524.343 747.580\n",
-      "40 636.161 62.659\n",
-      "50 -276.795 142.632\n",
-      "60 -434.015 54.631\n",
-      "70 -518.141 52.242\n",
-      "80 -570.395 27.263\n",
-      "90 -599.030 1.358\n",
-      "100 -618.720 0.670\n",
-      "step  N     T (K)     p (atm)   V (A3)    Ep (kcal/mol) Ek (kcal/mol) dens (g/cm3) \n",
-      "0     400   3.28e+02  2.94e+03  1.58e+04  -6.18e+02     0.0           1.68         \n",
-      "1000  400   3.28e+02  5.7e+03   1.58e+04  -4.91e+02     0.0           1.68         \n",
-      "2000  400   3.28e+02  6.54e+03  1.58e+04  -4.5e+02      0.0           1.68         \n",
-      "3000  400   3.28e+02  7.15e+03  1.58e+04  -4.23e+02     0.0           1.68         \n",
-      "4000  400   3.28e+02  7.25e+03  1.58e+04  -4.19e+02     0.0           1.68         \n",
-      "5000  400   3.28e+02  7.41e+03  1.58e+04  -4.13e+02     0.0           1.68         \n",
-      "6000  400   3.28e+02  7.63e+03  1.58e+04  -4.04e+02     0.0           1.68         \n",
-      "7000  400   3.28e+02  7.73e+03  1.58e+04  -4e+02        0.0           1.68         \n",
-      "8000  400   3.28e+02  7.78e+03  1.58e+04  -3.98e+02     0.0           1.68         \n",
-      "9000  400   3.28e+02  8.06e+03  1.58e+04  -3.82e+02     0.0           1.68         \n",
-      "10000 400   3.28e+02  8.02e+03  1.58e+04  -3.82e+02     0.0           1.68         \n",
-      "11000 400   3.28e+02  7.87e+03  1.58e+04  -3.89e+02     0.0           1.68         \n",
-      "12000 400   3.28e+02  7.98e+03  1.58e+04  -3.86e+02     0.0           1.68         \n",
-      "13000 400   3.28e+02  7.94e+03  1.58e+04  -3.89e+02     0.0           1.68         \n",
-      "14000 400   3.28e+02  8.17e+03  1.58e+04  -3.76e+02     0.0           1.68         \n",
-      "15000 400   3.28e+02  8.15e+03  1.58e+04  -3.76e+02     0.0           1.68         \n",
-      "16000 400   3.28e+02  8.57e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "17000 400   3.28e+02  8.46e+03  1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "18000 400   3.28e+02  8.55e+03  1.58e+04  -3.58e+02     0.0           1.68         \n",
-      "19000 400   3.28e+02  8.8e+03   1.58e+04  -3.46e+02     0.0           1.68         \n",
-      "20000 400   3.28e+02  8.71e+03  1.58e+04  -3.52e+02     0.0           1.68         \n"
-     ]
-    }
-   ],
-   "source": [
-    "# Minimization\n",
-    "em = MinimizeEnergy(maximum_steps=100,\n",
-    "                    thermo_period=10,\n",
-    "                    dumping_period=10,\n",
-    "    number_atoms=[N_atom],\n",
-    "    epsilon=[epsilon.magnitude], \n",
-    "    sigma=[sigma.magnitude],\n",
-    "    atom_mass=[m_argon.magnitude],\n",
-    "    box_dimensions=[box_size.magnitude,\n",
-    "                    box_size.magnitude,\n",
-    "                    box_size.magnitude],\n",
-    "    cut_off=cut_off.magnitude,\n",
-    "    data_folder=folder,\n",
-    ")\n",
-    "em.run()\n",
-    "\n",
-    "# Equilibration run\n",
-    "mc1 = MonteCarlo(maximum_steps=20000,\n",
-    "    dumping_period=1000,\n",
-    "    thermo_period=1000,\n",
-    "    neighbor=50,\n",
-    "    displace_mc = displace_mc.magnitude,\n",
-    "    desired_temperature = T.magnitude,\n",
-    "    number_atoms=[N_atom],\n",
-    "    epsilon=[epsilon.magnitude], \n",
-    "    sigma=[sigma.magnitude],\n",
-    "    atom_mass=[m_argon.magnitude],\n",
-    "    box_dimensions=[box_size.magnitude,\n",
-    "                    box_size.magnitude,\n",
-    "                    box_size.magnitude],\n",
-    "    initial_positions = em.atoms_positions*em.reference_distance,\n",
-    "    cut_off=cut_off.magnitude,\n",
-    "    data_folder=folder,\n",
-    ")\n",
-    "mc1.run()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "step  N     T (K)     p (atm)   V (A3)    Ep (kcal/mol) Ek (kcal/mol) dens (g/cm3) \n",
-      "0     400   3.28e+02  8.71e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "10    400   3.28e+02  8.69e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "20    400   3.28e+02  8.72e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "30    400   3.28e+02  8.74e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "40    400   3.28e+02  8.73e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "50    400   3.28e+02  8.77e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "60    400   3.28e+02  8.79e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "70    400   3.28e+02  8.8e+03   1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "80    400   3.28e+02  8.76e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "90    400   3.28e+02  8.72e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "100   400   3.28e+02  8.67e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "110   400   3.28e+02  8.67e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "120   400   3.28e+02  8.67e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "130   400   3.28e+02  8.62e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "140   400   3.28e+02  8.65e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "150   400   3.28e+02  8.64e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "160   400   3.28e+02  8.65e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "170   400   3.28e+02  8.65e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "180   400   3.28e+02  8.6e+03   1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "190   400   3.28e+02  8.59e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "200   400   3.28e+02  8.57e+03  1.58e+04  -3.58e+02     0.0           1.68         \n",
-      "210   400   3.28e+02  8.53e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "220   400   3.28e+02  8.54e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "230   400   3.28e+02  8.56e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "240   400   3.28e+02  8.52e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "250   400   3.28e+02  8.53e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "260   400   3.28e+02  8.54e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "270   400   3.28e+02  8.58e+03  1.58e+04  -3.58e+02     0.0           1.68         \n",
-      "280   400   3.28e+02  8.54e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "290   400   3.28e+02  8.59e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "300   400   3.28e+02  8.61e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "310   400   3.28e+02  8.61e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "320   400   3.28e+02  8.61e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "330   400   3.28e+02  8.6e+03   1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "340   400   3.28e+02  8.63e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "350   400   3.28e+02  8.6e+03   1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "360   400   3.28e+02  8.58e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "370   400   3.28e+02  8.6e+03   1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "380   400   3.28e+02  8.63e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "390   400   3.28e+02  8.68e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "400   400   3.28e+02  8.7e+03   1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "410   400   3.28e+02  8.66e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "420   400   3.28e+02  8.65e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "430   400   3.28e+02  8.7e+03   1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "440   400   3.28e+02  8.7e+03   1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "450   400   3.28e+02  8.69e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "460   400   3.28e+02  8.67e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "470   400   3.28e+02  8.65e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "480   400   3.28e+02  8.64e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "490   400   3.28e+02  8.71e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "500   400   3.28e+02  8.7e+03   1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "510   400   3.28e+02  8.74e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "520   400   3.28e+02  8.72e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "530   400   3.28e+02  8.73e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "540   400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "550   400   3.28e+02  8.75e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "560   400   3.28e+02  8.76e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "570   400   3.28e+02  8.83e+03  1.58e+04  -3.45e+02     0.0           1.68         \n",
-      "580   400   3.28e+02  8.83e+03  1.58e+04  -3.45e+02     0.0           1.68         \n",
-      "590   400   3.28e+02  8.83e+03  1.58e+04  -3.45e+02     0.0           1.68         \n",
-      "600   400   3.28e+02  8.84e+03  1.58e+04  -3.45e+02     0.0           1.68         \n",
-      "610   400   3.28e+02  8.85e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "620   400   3.28e+02  8.77e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "630   400   3.28e+02  8.77e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "640   400   3.28e+02  8.77e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "650   400   3.28e+02  8.78e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "660   400   3.28e+02  8.78e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "670   400   3.28e+02  8.74e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "680   400   3.28e+02  8.75e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "690   400   3.28e+02  8.76e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "700   400   3.28e+02  8.71e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "710   400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "720   400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "730   400   3.28e+02  8.7e+03   1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "740   400   3.28e+02  8.63e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "750   400   3.28e+02  8.59e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "760   400   3.28e+02  8.58e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "770   400   3.28e+02  8.58e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "780   400   3.28e+02  8.56e+03  1.58e+04  -3.58e+02     0.0           1.68         \n",
-      "790   400   3.28e+02  8.53e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "800   400   3.28e+02  8.53e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "810   400   3.28e+02  8.54e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "820   400   3.28e+02  8.54e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "830   400   3.28e+02  8.56e+03  1.58e+04  -3.58e+02     0.0           1.68         \n",
-      "840   400   3.28e+02  8.59e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "850   400   3.28e+02  8.62e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "860   400   3.28e+02  8.63e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "870   400   3.28e+02  8.62e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "880   400   3.28e+02  8.6e+03   1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "890   400   3.28e+02  8.6e+03   1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "900   400   3.28e+02  8.63e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "910   400   3.28e+02  8.62e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "920   400   3.28e+02  8.6e+03   1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "930   400   3.28e+02  8.58e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "940   400   3.28e+02  8.51e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "950   400   3.28e+02  8.5e+03   1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "960   400   3.28e+02  8.5e+03   1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "970   400   3.28e+02  8.5e+03   1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "980   400   3.28e+02  8.46e+03  1.58e+04  -3.63e+02     0.0           1.68         \n",
-      "990   400   3.28e+02  8.46e+03  1.58e+04  -3.62e+02     0.0           1.68         \n",
-      "1000  400   3.28e+02  8.51e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1010  400   3.28e+02  8.5e+03   1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1020  400   3.28e+02  8.5e+03   1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "1030  400   3.28e+02  8.52e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1040  400   3.28e+02  8.57e+03  1.58e+04  -3.58e+02     0.0           1.68         \n",
-      "1050  400   3.28e+02  8.52e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1060  400   3.28e+02  8.49e+03  1.58e+04  -3.62e+02     0.0           1.68         \n",
-      "1070  400   3.28e+02  8.49e+03  1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "1080  400   3.28e+02  8.54e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "1090  400   3.28e+02  8.61e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "1100  400   3.28e+02  8.6e+03   1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "1110  400   3.28e+02  8.63e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "1120  400   3.28e+02  8.6e+03   1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "1130  400   3.28e+02  8.61e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "1140  400   3.28e+02  8.62e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "1150  400   3.28e+02  8.59e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "1160  400   3.28e+02  8.61e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "1170  400   3.28e+02  8.63e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "1180  400   3.28e+02  8.62e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "1190  400   3.28e+02  8.63e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "1200  400   3.28e+02  8.62e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "1210  400   3.28e+02  8.64e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "1220  400   3.28e+02  8.66e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "1230  400   3.28e+02  8.64e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "1240  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1250  400   3.28e+02  8.69e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "1260  400   3.28e+02  8.67e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "1270  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1280  400   3.28e+02  8.67e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "1290  400   3.28e+02  8.72e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "1300  400   3.28e+02  8.78e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "1310  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "1320  400   3.28e+02  8.76e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "1330  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "1340  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "1350  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1360  400   3.28e+02  8.67e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "1370  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1380  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1390  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1400  400   3.28e+02  8.63e+03  1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "1410  400   3.28e+02  8.57e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "1420  400   3.28e+02  8.53e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "1430  400   3.28e+02  8.54e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "1440  400   3.28e+02  8.48e+03  1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "1450  400   3.28e+02  8.48e+03  1.58e+04  -3.62e+02     0.0           1.68         \n",
-      "1460  400   3.28e+02  8.49e+03  1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "1470  400   3.28e+02  8.48e+03  1.58e+04  -3.62e+02     0.0           1.68         \n",
-      "1480  400   3.28e+02  8.48e+03  1.58e+04  -3.62e+02     0.0           1.68         \n",
-      "1490  400   3.28e+02  8.47e+03  1.58e+04  -3.63e+02     0.0           1.68         \n",
-      "1500  400   3.28e+02  8.54e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "1510  400   3.28e+02  8.49e+03  1.58e+04  -3.62e+02     0.0           1.68         \n",
-      "1520  400   3.28e+02  8.47e+03  1.58e+04  -3.63e+02     0.0           1.68         \n",
-      "1530  400   3.28e+02  8.45e+03  1.58e+04  -3.64e+02     0.0           1.68         \n",
-      "1540  400   3.28e+02  8.43e+03  1.58e+04  -3.65e+02     0.0           1.68         \n",
-      "1550  400   3.28e+02  8.45e+03  1.58e+04  -3.64e+02     0.0           1.68         \n",
-      "1560  400   3.28e+02  8.43e+03  1.58e+04  -3.65e+02     0.0           1.68         \n",
-      "1570  400   3.28e+02  8.53e+03  1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "1580  400   3.28e+02  8.52e+03  1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "1590  400   3.28e+02  8.55e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1600  400   3.28e+02  8.54e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1610  400   3.28e+02  8.57e+03  1.58e+04  -3.58e+02     0.0           1.68         \n",
-      "1620  400   3.28e+02  8.58e+03  1.58e+04  -3.58e+02     0.0           1.68         \n",
-      "1630  400   3.28e+02  8.61e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "1640  400   3.28e+02  8.56e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "1650  400   3.28e+02  8.55e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "1660  400   3.28e+02  8.58e+03  1.58e+04  -3.58e+02     0.0           1.68         \n",
-      "1670  400   3.28e+02  8.55e+03  1.58e+04  -3.59e+02     0.0           1.68         \n",
-      "1680  400   3.28e+02  8.54e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1690  400   3.28e+02  8.54e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1700  400   3.28e+02  8.53e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1710  400   3.28e+02  8.51e+03  1.58e+04  -3.61e+02     0.0           1.68         \n",
-      "1720  400   3.28e+02  8.54e+03  1.58e+04  -3.6e+02      0.0           1.68         \n",
-      "1730  400   3.28e+02  8.59e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "1740  400   3.28e+02  8.6e+03   1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "1750  400   3.28e+02  8.59e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "1760  400   3.28e+02  8.62e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "1770  400   3.28e+02  8.61e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "1780  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1790  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1800  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1810  400   3.28e+02  8.71e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1820  400   3.28e+02  8.71e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1830  400   3.28e+02  8.72e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "1840  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1850  400   3.28e+02  8.74e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "1860  400   3.28e+02  8.72e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "1870  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1880  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1890  400   3.28e+02  8.71e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "1900  400   3.28e+02  8.71e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "1910  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "1920  400   3.28e+02  8.72e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "1930  400   3.28e+02  8.72e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "1940  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "1950  400   3.28e+02  8.76e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "1960  400   3.28e+02  8.74e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "1970  400   3.28e+02  8.72e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "1980  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "1990  400   3.28e+02  8.79e+03  1.58e+04  -3.46e+02     0.0           1.68         \n",
-      "2000  400   3.28e+02  8.84e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2010  400   3.28e+02  8.83e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2020  400   3.28e+02  8.83e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2030  400   3.28e+02  8.84e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2040  400   3.28e+02  8.85e+03  1.58e+04  -3.43e+02     0.0           1.68         \n",
-      "2050  400   3.28e+02  8.85e+03  1.58e+04  -3.43e+02     0.0           1.68         \n",
-      "2060  400   3.28e+02  8.84e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2070  400   3.28e+02  8.87e+03  1.58e+04  -3.42e+02     0.0           1.68         \n",
-      "2080  400   3.28e+02  8.89e+03  1.58e+04  -3.41e+02     0.0           1.68         \n",
-      "2090  400   3.28e+02  8.88e+03  1.58e+04  -3.42e+02     0.0           1.68         \n",
-      "2100  400   3.28e+02  8.87e+03  1.58e+04  -3.42e+02     0.0           1.68         \n",
-      "2110  400   3.28e+02  8.88e+03  1.58e+04  -3.42e+02     0.0           1.68         \n",
-      "2120  400   3.28e+02  8.82e+03  1.58e+04  -3.45e+02     0.0           1.68         \n",
-      "2130  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2140  400   3.28e+02  8.79e+03  1.58e+04  -3.46e+02     0.0           1.68         \n",
-      "2150  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2160  400   3.28e+02  8.76e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "2170  400   3.28e+02  8.79e+03  1.58e+04  -3.46e+02     0.0           1.68         \n",
-      "2180  400   3.28e+02  8.71e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "2190  400   3.28e+02  8.7e+03   1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "2200  400   3.28e+02  8.67e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "2210  400   3.28e+02  8.65e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2220  400   3.28e+02  8.72e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "2230  400   3.28e+02  8.72e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "2240  400   3.28e+02  8.75e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "2250  400   3.28e+02  8.75e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "2260  400   3.28e+02  8.76e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2270  400   3.28e+02  8.74e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "2280  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "2290  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "2300  400   3.28e+02  8.67e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "2310  400   3.28e+02  8.65e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2320  400   3.28e+02  8.67e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "2330  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "2340  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "2350  400   3.28e+02  8.74e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "2360  400   3.28e+02  8.77e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "2370  400   3.28e+02  8.76e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "2380  400   3.28e+02  8.79e+03  1.58e+04  -3.46e+02     0.0           1.68         \n",
-      "2390  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2400  400   3.28e+02  8.77e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "2410  400   3.28e+02  8.71e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "2420  400   3.28e+02  8.66e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2430  400   3.28e+02  8.73e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "2440  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "2450  400   3.28e+02  8.68e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "2460  400   3.28e+02  8.7e+03   1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "2470  400   3.28e+02  8.66e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2480  400   3.28e+02  8.66e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2490  400   3.28e+02  8.66e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2500  400   3.28e+02  8.64e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "2510  400   3.28e+02  8.64e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "2520  400   3.28e+02  8.64e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2530  400   3.28e+02  8.66e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2540  400   3.28e+02  8.72e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "2550  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2560  400   3.28e+02  8.84e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2570  400   3.28e+02  8.84e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2580  400   3.28e+02  8.83e+03  1.58e+04  -3.45e+02     0.0           1.68         \n",
-      "2590  400   3.28e+02  8.84e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2600  400   3.28e+02  8.79e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2610  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2620  400   3.28e+02  8.67e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "2630  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "2640  400   3.28e+02  8.67e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "2650  400   3.28e+02  8.71e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "2660  400   3.28e+02  8.72e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "2670  400   3.28e+02  8.72e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "2680  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "2690  400   3.28e+02  8.76e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "2700  400   3.28e+02  8.76e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "2710  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "2720  400   3.28e+02  8.79e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2730  400   3.28e+02  8.85e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2740  400   3.28e+02  8.86e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "2750  400   3.28e+02  8.83e+03  1.58e+04  -3.45e+02     0.0           1.68         \n",
-      "2760  400   3.28e+02  8.79e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2770  400   3.28e+02  8.76e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "2780  400   3.28e+02  8.65e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2790  400   3.28e+02  8.65e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2800  400   3.28e+02  8.66e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "2810  400   3.28e+02  8.68e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "2820  400   3.28e+02  8.67e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "2830  400   3.28e+02  8.61e+03  1.58e+04  -3.54e+02     0.0           1.68         \n",
-      "2840  400   3.28e+02  8.56e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "2850  400   3.28e+02  8.56e+03  1.58e+04  -3.57e+02     0.0           1.68         \n",
-      "2860  400   3.28e+02  8.57e+03  1.58e+04  -3.56e+02     0.0           1.68         \n",
-      "2870  400   3.28e+02  8.6e+03   1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "2880  400   3.28e+02  8.63e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2890  400   3.28e+02  8.6e+03   1.58e+04  -3.55e+02     0.0           1.68         \n",
-      "2900  400   3.28e+02  8.64e+03  1.58e+04  -3.53e+02     0.0           1.68         \n",
-      "2910  400   3.28e+02  8.66e+03  1.58e+04  -3.52e+02     0.0           1.68         \n",
-      "2920  400   3.28e+02  8.69e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "2930  400   3.28e+02  8.75e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2940  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2950  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2960  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2970  400   3.28e+02  8.76e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2980  400   3.28e+02  8.76e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "2990  400   3.28e+02  8.76e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "3000  400   3.28e+02  8.76e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "3010  400   3.28e+02  8.74e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3020  400   3.28e+02  8.71e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "3030  400   3.28e+02  8.7e+03   1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "3040  400   3.28e+02  8.7e+03   1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "3050  400   3.28e+02  8.75e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3060  400   3.28e+02  8.72e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3070  400   3.28e+02  8.7e+03   1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "3080  400   3.28e+02  8.7e+03   1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "3090  400   3.28e+02  8.71e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3100  400   3.28e+02  8.7e+03   1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "3110  400   3.28e+02  8.72e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3120  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "3130  400   3.28e+02  8.75e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3140  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3150  400   3.28e+02  8.75e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3160  400   3.28e+02  8.76e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "3170  400   3.28e+02  8.74e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3180  400   3.28e+02  8.78e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "3190  400   3.28e+02  8.74e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3200  400   3.28e+02  8.8e+03   1.58e+04  -3.46e+02     0.0           1.68         \n",
-      "3210  400   3.28e+02  8.8e+03   1.58e+04  -3.46e+02     0.0           1.68         \n",
-      "3220  400   3.28e+02  8.8e+03   1.58e+04  -3.45e+02     0.0           1.68         \n",
-      "3230  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "3240  400   3.28e+02  8.75e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3250  400   3.28e+02  8.74e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3260  400   3.28e+02  8.72e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3270  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3280  400   3.28e+02  8.75e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3290  400   3.28e+02  8.72e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3300  400   3.28e+02  8.71e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "3310  400   3.28e+02  8.74e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3320  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3330  400   3.28e+02  8.71e+03  1.58e+04  -3.5e+02      0.0           1.68         \n",
-      "3340  400   3.28e+02  8.69e+03  1.58e+04  -3.51e+02     0.0           1.68         \n",
-      "3350  400   3.28e+02  8.73e+03  1.58e+04  -3.49e+02     0.0           1.68         \n",
-      "3360  400   3.28e+02  8.77e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "3370  400   3.28e+02  8.78e+03  1.58e+04  -3.46e+02     0.0           1.68         \n",
-      "3380  400   3.28e+02  8.75e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3390  400   3.28e+02  8.75e+03  1.58e+04  -3.48e+02     0.0           1.68         \n",
-      "3400  400   3.28e+02  8.78e+03  1.58e+04  -3.46e+02     0.0           1.68         \n",
-      "3410  400   3.28e+02  8.83e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "3420  400   3.28e+02  8.76e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "3430  400   3.28e+02  8.76e+03  1.58e+04  -3.47e+02     0.0           1.68         \n",
-      "3440  400   3.28e+02  8.82e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "3450  400   3.28e+02  8.83e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "3460  400   3.28e+02  8.81e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "3470  400   3.28e+02  8.8e+03   1.58e+04  -3.45e+02     0.0           1.68         \n",
-      "3480  400   3.28e+02  8.82e+03  1.58e+04  -3.44e+02     0.0           1.68         \n",
-      "3490  400   3.28e+02  8.84e+03  1.58e+04  -3.43e+02     0.0           1.68         \n",
-      "3500  400   3.28e+02  8.89e+03  1.58e+04  -3.41e+02     0.0           1.68         \n",
-      "3510  400   3.28e+02  8.89e+03  1.58e+04  -3.41e+02     0.0           1.68         \n",
-      "3520  400   3.28e+02  8.9e+03   1.58e+04  -3.4e+02      0.0           1.68         \n",
-      "3530  400   3.28e+02  8.96e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3540  400   3.28e+02  8.88e+03  1.58e+04  -3.42e+02     0.0           1.68         \n",
-      "3550  400   3.28e+02  8.88e+03  1.58e+04  -3.42e+02     0.0           1.68         \n",
-      "3560  400   3.28e+02  8.9e+03   1.58e+04  -3.41e+02     0.0           1.68         \n",
-      "3570  400   3.28e+02  8.89e+03  1.58e+04  -3.41e+02     0.0           1.68         \n",
-      "3580  400   3.28e+02  8.97e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3590  400   3.28e+02  8.97e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3600  400   3.28e+02  8.96e+03  1.58e+04  -3.38e+02     0.0           1.68         \n",
-      "3610  400   3.28e+02  8.94e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "3620  400   3.28e+02  8.98e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3630  400   3.28e+02  8.98e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "3640  400   3.28e+02  8.98e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3650  400   3.28e+02  9e+03     1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "3660  400   3.28e+02  9e+03     1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "3670  400   3.28e+02  8.98e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3680  400   3.28e+02  8.96e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3690  400   3.28e+02  8.98e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "3700  400   3.28e+02  9e+03     1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "3710  400   3.28e+02  9e+03     1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "3720  400   3.28e+02  8.95e+03  1.58e+04  -3.38e+02     0.0           1.68         \n",
-      "3730  400   3.28e+02  9e+03     1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "3740  400   3.28e+02  8.99e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "3750  400   3.28e+02  8.98e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "3760  400   3.28e+02  8.99e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "3770  400   3.28e+02  8.92e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "3780  400   3.28e+02  8.96e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3790  400   3.28e+02  8.95e+03  1.58e+04  -3.38e+02     0.0           1.68         \n",
-      "3800  400   3.28e+02  8.92e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "3810  400   3.28e+02  8.94e+03  1.58e+04  -3.38e+02     0.0           1.68         \n",
-      "3820  400   3.28e+02  8.97e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3830  400   3.28e+02  8.99e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3840  400   3.28e+02  9.02e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "3850  400   3.28e+02  9.02e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "3860  400   3.28e+02  8.99e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3870  400   3.28e+02  8.94e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "3880  400   3.28e+02  8.93e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "3890  400   3.28e+02  8.92e+03  1.58e+04  -3.4e+02      0.0           1.68         \n",
-      "3900  400   3.28e+02  8.94e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "3910  400   3.28e+02  8.98e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3920  400   3.28e+02  9.01e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "3930  400   3.28e+02  9.04e+03  1.58e+04  -3.34e+02     0.0           1.68         \n",
-      "3940  400   3.28e+02  9.07e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "3950  400   3.28e+02  9.05e+03  1.58e+04  -3.33e+02     0.0           1.68         \n",
-      "3960  400   3.28e+02  9.08e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "3970  400   3.28e+02  9.03e+03  1.58e+04  -3.34e+02     0.0           1.68         \n",
-      "3980  400   3.28e+02  8.97e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "3990  400   3.28e+02  9e+03     1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4000  400   3.28e+02  9e+03     1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4010  400   3.28e+02  8.97e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4020  400   3.28e+02  8.97e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4030  400   3.28e+02  8.97e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4040  400   3.28e+02  8.98e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "4050  400   3.28e+02  8.92e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "4060  400   3.28e+02  8.96e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4070  400   3.28e+02  8.98e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4080  400   3.28e+02  8.97e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4090  400   3.28e+02  8.91e+03  1.58e+04  -3.4e+02      0.0           1.68         \n",
-      "4100  400   3.28e+02  8.94e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "4110  400   3.28e+02  8.93e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "4120  400   3.28e+02  8.94e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "4130  400   3.28e+02  9e+03     1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "4140  400   3.28e+02  9.06e+03  1.58e+04  -3.33e+02     0.0           1.68         \n",
-      "4150  400   3.28e+02  9.07e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4160  400   3.28e+02  9.08e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4170  400   3.28e+02  9.07e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4180  400   3.28e+02  9.07e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4190  400   3.28e+02  9.05e+03  1.58e+04  -3.33e+02     0.0           1.68         \n",
-      "4200  400   3.28e+02  9.06e+03  1.58e+04  -3.33e+02     0.0           1.68         \n",
-      "4210  400   3.28e+02  9.12e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4220  400   3.28e+02  9.11e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4230  400   3.28e+02  9.12e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4240  400   3.28e+02  9.11e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4250  400   3.28e+02  9.13e+03  1.58e+04  -3.29e+02     0.0           1.68         \n",
-      "4260  400   3.28e+02  9.14e+03  1.58e+04  -3.29e+02     0.0           1.68         \n",
-      "4270  400   3.28e+02  9.13e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4280  400   3.28e+02  9.2e+03   1.58e+04  -3.26e+02     0.0           1.68         \n",
-      "4290  400   3.28e+02  9.17e+03  1.58e+04  -3.28e+02     0.0           1.68         \n",
-      "4300  400   3.28e+02  9.17e+03  1.58e+04  -3.28e+02     0.0           1.68         \n",
-      "4310  400   3.28e+02  9.12e+03  1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4320  400   3.28e+02  9.12e+03  1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4330  400   3.28e+02  9.11e+03  1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4340  400   3.28e+02  9.09e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4350  400   3.28e+02  9.06e+03  1.58e+04  -3.33e+02     0.0           1.68         \n",
-      "4360  400   3.28e+02  9.08e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4370  400   3.28e+02  9.12e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4380  400   3.28e+02  9.12e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4390  400   3.28e+02  9.1e+03   1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4400  400   3.28e+02  9.1e+03   1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4410  400   3.28e+02  9.11e+03  1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4420  400   3.28e+02  9.11e+03  1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4430  400   3.28e+02  9.12e+03  1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4440  400   3.28e+02  9.09e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4450  400   3.28e+02  9.09e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4460  400   3.28e+02  9.12e+03  1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4470  400   3.28e+02  9.14e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4480  400   3.28e+02  9.12e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4490  400   3.28e+02  9.08e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4500  400   3.28e+02  9.09e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4510  400   3.28e+02  9.08e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4520  400   3.28e+02  9.08e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4530  400   3.28e+02  9.08e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4540  400   3.28e+02  9.07e+03  1.58e+04  -3.33e+02     0.0           1.68         \n",
-      "4550  400   3.28e+02  9.05e+03  1.58e+04  -3.34e+02     0.0           1.68         \n",
-      "4560  400   3.28e+02  9.08e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4570  400   3.28e+02  9.12e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4580  400   3.28e+02  9.14e+03  1.58e+04  -3.29e+02     0.0           1.68         \n",
-      "4590  400   3.28e+02  9.11e+03  1.58e+04  -3.31e+02     0.0           1.68         \n",
-      "4600  400   3.28e+02  9.11e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4610  400   3.28e+02  9.12e+03  1.58e+04  -3.3e+02      0.0           1.68         \n",
-      "4620  400   3.28e+02  9.14e+03  1.58e+04  -3.29e+02     0.0           1.68         \n",
-      "4630  400   3.28e+02  9.09e+03  1.58e+04  -3.32e+02     0.0           1.68         \n",
-      "4640  400   3.28e+02  9.06e+03  1.58e+04  -3.33e+02     0.0           1.68         \n",
-      "4650  400   3.28e+02  9.05e+03  1.58e+04  -3.34e+02     0.0           1.68         \n",
-      "4660  400   3.28e+02  9.03e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4670  400   3.28e+02  9.05e+03  1.58e+04  -3.34e+02     0.0           1.68         \n",
-      "4680  400   3.28e+02  9.02e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4690  400   3.28e+02  9.02e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "4700  400   3.28e+02  9.01e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "4710  400   3.28e+02  9e+03     1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4720  400   3.28e+02  9.03e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4730  400   3.28e+02  9.02e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "4740  400   3.28e+02  9.04e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4750  400   3.28e+02  8.99e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4760  400   3.28e+02  8.95e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "4770  400   3.28e+02  8.93e+03  1.58e+04  -3.4e+02      0.0           1.68         \n",
-      "4780  400   3.28e+02  8.96e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "4790  400   3.28e+02  8.99e+03  1.58e+04  -3.38e+02     0.0           1.68         \n",
-      "4800  400   3.28e+02  8.95e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "4810  400   3.28e+02  8.95e+03  1.58e+04  -3.4e+02      0.0           1.68         \n",
-      "4820  400   3.28e+02  8.95e+03  1.58e+04  -3.4e+02      0.0           1.68         \n",
-      "4830  400   3.28e+02  9e+03     1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4840  400   3.28e+02  8.98e+03  1.58e+04  -3.38e+02     0.0           1.68         \n",
-      "4850  400   3.28e+02  8.97e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "4860  400   3.28e+02  8.94e+03  1.58e+04  -3.4e+02      0.0           1.68         \n",
-      "4870  400   3.28e+02  8.95e+03  1.58e+04  -3.39e+02     0.0           1.68         \n",
-      "4880  400   3.28e+02  9.02e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4890  400   3.28e+02  9.01e+03  1.58e+04  -3.37e+02     0.0           1.68         \n",
-      "4900  400   3.28e+02  9.02e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "4910  400   3.28e+02  9.05e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4920  400   3.28e+02  9.03e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "4930  400   3.28e+02  9.02e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "4940  400   3.28e+02  9.02e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "4950  400   3.28e+02  9.05e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4960  400   3.28e+02  9.05e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4970  400   3.28e+02  9.05e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4980  400   3.28e+02  9.06e+03  1.58e+04  -3.35e+02     0.0           1.68         \n",
-      "4990  400   3.28e+02  9.03e+03  1.58e+04  -3.36e+02     0.0           1.68         \n",
-      "5000  400   3.28e+02  9.04e+03  1.58e+04  -3.36e+02     0.0           1.68         \n"
-     ]
-    }
-   ],
-   "source": [
-    "# Short production run\n",
-    "mc2 = MonteCarlo(maximum_steps=5000,\n",
-    "    dumping_period=10,\n",
-    "    thermo_period=10,\n",
-    "    neighbor=50,\n",
-    "    displace_mc = displace_mc.magnitude,\n",
-    "    desired_temperature = T.magnitude,\n",
-    "    number_atoms=[N_atom],\n",
-    "    epsilon=[epsilon.magnitude], \n",
-    "    sigma=[sigma.magnitude],\n",
-    "    atom_mass=[m_argon.magnitude],\n",
-    "    box_dimensions=[box_size.magnitude,\n",
-    "                    box_size.magnitude,\n",
-    "                    box_size.magnitude],\n",
-    "    initial_positions = mc1.atoms_positions*mc1.reference_distance,\n",
-    "        cut_off=cut_off.magnitude,\n",
-    "        data_folder=folder,\n",
-    "    )\n",
-    "mc2.run()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/integration_tests/test_monte_carlo_move.py b/integration_tests/test_monte_carlo_move.py
index 0dd00f4..abfa96b 100644
--- a/integration_tests/test_monte_carlo_move.py
+++ b/integration_tests/test_monte_carlo_move.py
@@ -33,7 +33,7 @@ def setUp(self):
         # Initialize the MonteCarlo object
         self.mc = MonteCarlo(
             ureg = ureg,
-            maximum_steps = 100000,
+            maximum_steps = 10000,
             thermo_period = 1000,
             dumping_period = 1000,
             number_atoms = [nmb_1],
diff --git a/pictures/Minimize/convert_transparent.sh b/pictures/Minimize/convert_transparent.sh
deleted file mode 100755
index 45feddb..0000000
--- a/pictures/Minimize/convert_transparent.sh
+++ /dev/null
@@ -1,18 +0,0 @@
-#!/bin/bash
-
-export LC_NUMERIC="en_US.UTF-8"
-set -e
-
-# 1) Generate white background movie
-for file in _light.*.ppm; 
-do 
-	convert -resize 50% $file -transparent white ${file:0:12}.png;
-done
-img2webp -o avatar.webp -q 30 -mixed -d 25 _light*.png
-
-# 2) Generate black background movie
-for file in _dark.*.ppm; 
-do 
-	convert -resize 50% $file -transparent black ${file:0:11}.png;
-done
-img2webp -o avatar-dm.webp -q 30 -mixed -d 25 _dark*.png
diff --git a/pictures/Minimize/state.vmd b/pictures/Minimize/state.vmd
deleted file mode 100644
index f74adf5..0000000
--- a/pictures/Minimize/state.vmd
+++ /dev/null
@@ -1,562 +0,0 @@
-#!/usr/local/bin/vmd
-# VMD script written by save_state $Revision: 1.48 $
-# VMD version: 1.9.4a57
-set viewplist {}
-set fixedlist {}
-proc vmdrestoremymaterials {} {
-  set mlist { Opaque Transparent BrushedMetal Diffuse Ghost Glass1 Glass2 Glass3 Glossy HardPlastic MetallicPastel Steel Translucent Edgy EdgyShiny EdgyGlass Goodsell AOShiny AOChalky AOEdgy BlownGlass GlassBubble RTChrome }
-  set mymlist [material list]
-  foreach mat $mlist {
-    if { [lsearch $mymlist $mat] == -1 } { 
-      material add $mat
-    }
-  }
-  material change ambient Opaque 0.000000
-  material change diffuse Opaque 0.560000
-  material change specular Opaque 0.120000
-  material change shininess Opaque 0.290000
-  material change mirror Opaque 0.000000
-  material change opacity Opaque 1.000000
-  material change outline Opaque 0.000000
-  material change outlinewidth Opaque 0.000000
-  material change transmode Opaque 0.000000
-  material change ambient Transparent 0.000000
-  material change diffuse Transparent 0.650000
-  material change specular Transparent 0.500000
-  material change shininess Transparent 0.534020
-  material change mirror Transparent 0.000000
-  material change opacity Transparent 0.300000
-  material change outline Transparent 0.000000
-  material change outlinewidth Transparent 0.000000
-  material change transmode Transparent 0.000000
-  material change ambient BrushedMetal 0.080000
-  material change diffuse BrushedMetal 0.390000
-  material change specular BrushedMetal 0.340000
-  material change shininess BrushedMetal 0.150000
-  material change mirror BrushedMetal 0.000000
-  material change opacity BrushedMetal 1.000000
-  material change outline BrushedMetal 0.000000
-  material change outlinewidth BrushedMetal 0.000000
-  material change transmode BrushedMetal 0.000000
-  material change ambient Diffuse 0.000000
-  material change diffuse Diffuse 0.620000
-  material change specular Diffuse 0.000000
-  material change shininess Diffuse 0.530000
-  material change mirror Diffuse 0.000000
-  material change opacity Diffuse 1.000000
-  material change outline Diffuse 0.000000
-  material change outlinewidth Diffuse 0.000000
-  material change transmode Diffuse 0.000000
-  material change ambient Ghost 0.000000
-  material change diffuse Ghost 0.000000
-  material change specular Ghost 1.000000
-  material change shininess Ghost 0.230000
-  material change mirror Ghost 0.000000
-  material change opacity Ghost 0.100000
-  material change outline Ghost 0.000000
-  material change outlinewidth Ghost 0.000000
-  material change transmode Ghost 0.000000
-  material change ambient Glass1 0.000000
-  material change diffuse Glass1 0.500000
-  material change specular Glass1 0.650000
-  material change shininess Glass1 0.530000
-  material change mirror Glass1 0.000000
-  material change opacity Glass1 0.150000
-  material change outline Glass1 0.000000
-  material change outlinewidth Glass1 0.000000
-  material change transmode Glass1 0.000000
-  material change ambient Glass2 0.520000
-  material change diffuse Glass2 0.760000
-  material change specular Glass2 0.220000
-  material change shininess Glass2 0.590000
-  material change mirror Glass2 0.000000
-  material change opacity Glass2 0.680000
-  material change outline Glass2 0.000000
-  material change outlinewidth Glass2 0.000000
-  material change transmode Glass2 0.000000
-  material change ambient Glass3 0.150000
-  material change diffuse Glass3 0.250000
-  material change specular Glass3 0.750000
-  material change shininess Glass3 0.800000
-  material change mirror Glass3 0.000000
-  material change opacity Glass3 0.500000
-  material change outline Glass3 0.000000
-  material change outlinewidth Glass3 0.000000
-  material change transmode Glass3 0.000000
-  material change ambient Glossy 0.000000
-  material change diffuse Glossy 0.650000
-  material change specular Glossy 1.000000
-  material change shininess Glossy 0.880000
-  material change mirror Glossy 0.000000
-  material change opacity Glossy 1.000000
-  material change outline Glossy 0.000000
-  material change outlinewidth Glossy 0.000000
-  material change transmode Glossy 0.000000
-  material change ambient HardPlastic 0.000000
-  material change diffuse HardPlastic 0.560000
-  material change specular HardPlastic 0.280000
-  material change shininess HardPlastic 0.690000
-  material change mirror HardPlastic 0.000000
-  material change opacity HardPlastic 1.000000
-  material change outline HardPlastic 0.000000
-  material change outlinewidth HardPlastic 0.000000
-  material change transmode HardPlastic 0.000000
-  material change ambient MetallicPastel 0.000000
-  material change diffuse MetallicPastel 0.260000
-  material change specular MetallicPastel 0.550000
-  material change shininess MetallicPastel 0.190000
-  material change mirror MetallicPastel 0.000000
-  material change opacity MetallicPastel 1.000000
-  material change outline MetallicPastel 0.000000
-  material change outlinewidth MetallicPastel 0.000000
-  material change transmode MetallicPastel 0.000000
-  material change ambient Steel 0.250000
-  material change diffuse Steel 0.000000
-  material change specular Steel 0.380000
-  material change shininess Steel 0.320000
-  material change mirror Steel 0.000000
-  material change opacity Steel 1.000000
-  material change outline Steel 0.000000
-  material change outlinewidth Steel 0.000000
-  material change transmode Steel 0.000000
-  material change ambient Translucent 0.000000
-  material change diffuse Translucent 0.700000
-  material change specular Translucent 0.600000
-  material change shininess Translucent 0.300000
-  material change mirror Translucent 0.000000
-  material change opacity Translucent 0.800000
-  material change outline Translucent 0.000000
-  material change outlinewidth Translucent 0.000000
-  material change transmode Translucent 0.000000
-  material change ambient Edgy 0.000000
-  material change diffuse Edgy 0.660000
-  material change specular Edgy 0.000000
-  material change shininess Edgy 0.750000
-  material change mirror Edgy 0.000000
-  material change opacity Edgy 1.000000
-  material change outline Edgy 0.620000
-  material change outlinewidth Edgy 0.940000
-  material change transmode Edgy 0.000000
-  material change ambient EdgyShiny 0.000000
-  material change diffuse EdgyShiny 0.660000
-  material change specular EdgyShiny 0.960000
-  material change shininess EdgyShiny 0.750000
-  material change mirror EdgyShiny 0.000000
-  material change opacity EdgyShiny 1.000000
-  material change outline EdgyShiny 0.760000
-  material change outlinewidth EdgyShiny 0.940000
-  material change transmode EdgyShiny 0.000000
-  material change ambient EdgyGlass 0.000000
-  material change diffuse EdgyGlass 0.660000
-  material change specular EdgyGlass 0.500000
-  material change shininess EdgyGlass 0.750000
-  material change mirror EdgyGlass 0.000000
-  material change opacity EdgyGlass 0.620000
-  material change outline EdgyGlass 0.620000
-  material change outlinewidth EdgyGlass 0.940000
-  material change transmode EdgyGlass 0.000000
-  material change ambient Goodsell 0.520000
-  material change diffuse Goodsell 1.000000
-  material change specular Goodsell 0.000000
-  material change shininess Goodsell 0.000000
-  material change mirror Goodsell 0.000000
-  material change opacity Goodsell 1.000000
-  material change outline Goodsell 4.000000
-  material change outlinewidth Goodsell 0.900000
-  material change transmode Goodsell 0.000000
-  material change ambient AOShiny 0.000000
-  material change diffuse AOShiny 0.850000
-  material change specular AOShiny 0.200000
-  material change shininess AOShiny 0.530000
-  material change mirror AOShiny 0.000000
-  material change opacity AOShiny 1.000000
-  material change outline AOShiny 0.000000
-  material change outlinewidth AOShiny 0.000000
-  material change transmode AOShiny 0.000000
-  material change ambient AOChalky 0.000000
-  material change diffuse AOChalky 0.850000
-  material change specular AOChalky 0.000000
-  material change shininess AOChalky 0.530000
-  material change mirror AOChalky 0.000000
-  material change opacity AOChalky 1.000000
-  material change outline AOChalky 0.000000
-  material change outlinewidth AOChalky 0.000000
-  material change transmode AOChalky 0.000000
-  material change ambient AOEdgy 0.000000
-  material change diffuse AOEdgy 0.900000
-  material change specular AOEdgy 0.200000
-  material change shininess AOEdgy 0.530000
-  material change mirror AOEdgy 0.000000
-  material change opacity AOEdgy 1.000000
-  material change outline AOEdgy 0.620000
-  material change outlinewidth AOEdgy 0.930000
-  material change transmode AOEdgy 0.000000
-  material change ambient BlownGlass 0.040000
-  material change diffuse BlownGlass 0.340000
-  material change specular BlownGlass 1.000000
-  material change shininess BlownGlass 1.000000
-  material change mirror BlownGlass 0.000000
-  material change opacity BlownGlass 0.100000
-  material change outline BlownGlass 0.000000
-  material change outlinewidth BlownGlass 0.000000
-  material change transmode BlownGlass 1.000000
-  material change ambient GlassBubble 0.250000
-  material change diffuse GlassBubble 0.340000
-  material change specular GlassBubble 1.000000
-  material change shininess GlassBubble 1.000000
-  material change mirror GlassBubble 0.000000
-  material change opacity GlassBubble 0.040000
-  material change outline GlassBubble 0.000000
-  material change outlinewidth GlassBubble 0.000000
-  material change transmode GlassBubble 1.000000
-  material change ambient RTChrome 0.000000
-  material change diffuse RTChrome 0.650000
-  material change specular RTChrome 0.500000
-  material change shininess RTChrome 0.530000
-  material change mirror RTChrome 0.700000
-  material change opacity RTChrome 1.000000
-  material change outline RTChrome 0.000000
-  material change outlinewidth RTChrome 0.000000
-  material change transmode RTChrome 0.000000
-}
-vmdrestoremymaterials
-# Atom selection macros
-atomselect macro at {resname ADE A THY T}
-atomselect macro acidic {resname ASP GLU}
-atomselect macro cyclic {resname HIS PHE PRO TRP TYR}
-atomselect macro acyclic {protein and not cyclic}
-atomselect macro aliphatic {resname ALA GLY ILE LEU VAL}
-atomselect macro alpha {protein and name CA}
-atomselect macro amino protein
-atomselect macro aromatic {resname HIS PHE TRP TYR}
-atomselect macro basic {resname ARG HIS LYS HSP}
-atomselect macro bonded {numbonds > 0}
-atomselect macro buried {resname ALA LEU VAL ILE PHE CYS MET TRP}
-atomselect macro cg {resname CYT C GUA G}
-atomselect macro charged {basic or acidic}
-atomselect macro hetero {not (protein or nucleic)}
-atomselect macro hydrophobic {resname ALA LEU VAL ILE PRO PHE MET TRP}
-atomselect macro small {resname ALA GLY SER}
-atomselect macro medium {resname VAL THR ASP ASN PRO CYS ASX PCA HYP}
-atomselect macro large {protein and not (small or medium)}
-atomselect macro neutral {resname VAL PHE GLN TYR HIS CYS MET TRP ASX GLX PCA HYP}
-atomselect macro polar {protein and not hydrophobic}
-atomselect macro purine {resname ADE A GUA G}
-atomselect macro pyrimidine {resname CYT C THY T URA U}
-atomselect macro surface {protein and not buried}
-atomselect macro lipid {resname DLPE DMPC DPPC GPC LPPC PALM PC PGCL POPC POPE}
-atomselect macro lipids lipid
-atomselect macro ion {resname AL BA CA CAL CD CES CLA CL CO CS CU CU1 CUA HG IN IOD K LIT MG MN3 MO3 MO4 MO5 MO6 NA NAW OC7 PB POT PT RB SOD TB TL WO4 YB ZN ZN1 ZN2}
-atomselect macro ions ion
-atomselect macro sugar {resname AGLC}
-atomselect macro solvent {not (protein or sugar or nucleic or lipid)}
-atomselect macro glycan {resname NAG BGLN FUC AFUC MAN AMAN BMA BMAN}
-atomselect macro carbon {name "C.*" and not ion}
-atomselect macro hydrogen {name "[0-9]?H.*"}
-atomselect macro nitrogen {name "N.*"}
-atomselect macro oxygen {name "O.*"}
-atomselect macro sulfur {name "S.*" and not ion}
-atomselect macro noh {not hydrogen}
-atomselect macro heme {resname HEM HEME}
-atomselect macro conformationall {altloc ""}
-atomselect macro conformationA {altloc "" or altloc "A"}
-atomselect macro conformationB {altloc "" or altloc "B"}
-atomselect macro conformationC {altloc "" or altloc "C"}
-atomselect macro conformationD {altloc "" or altloc "D"}
-atomselect macro conformationE {altloc "" or altloc "E"}
-atomselect macro conformationF {altloc "" or altloc "F"}
-atomselect macro drude {type DRUD or type LP}
-atomselect macro unparametrized beta<1
-atomselect macro addedmolefacture {occupancy 0.8}
-atomselect macro qwikmd_protein {(not name QWIKMDDELETE and protein)}
-atomselect macro qwikmd_nucleic {(not name QWIKMDDELETE and nucleic)}
-atomselect macro qwikmd_glycan {(not name QWIKMDDELETE and glycan)}
-atomselect macro qwikmd_lipid {(not name QWIKMDDELETE and lipid)}
-atomselect macro qwikmd_hetero {(not name QWIKMDDELETE and hetero and not qwikmd_protein and not qwikmd_lipid and not qwikmd_nucleic and not qwikmd_glycan and not water)}
-# Display settings
-display eyesep       0.065000
-display focallength  2.000000
-display height       3.500000
-display distance     -2.000000
-display projection   Orthographic
-display nearclip set 0.500000
-display farclip  set 10.000000
-display depthcue   off
-display cuestart   0.500000
-display cueend     10.000000
-display cuestart   0.500000
-display cueend     10.000000
-display cuedensity 0.320000
-display cuemode    Exp2
-display shadows off
-display ambientocclusion off
-display aoambient 0.800000
-display aodirect 0.300000
-display dof off
-display dof_fnumber 64.000000
-display dof_focaldist 0.700000
-mol new dump.min.lammpstrj type lammpstrj first 0 last -1 step 1 filebonds 1 autobonds 1 waitfor all
-graphics top color 0
-graphics top material 0
-graphics top line {-10.000000 -10.000000 -10.000000} {10.000000 -10.000000 -10.000000} style solid width 4
-graphics top line {-10.000000 -10.000000 -10.000000} {-10.000000 10.000000 -10.000000} style solid width 4
-graphics top line {-10.000000 -10.000000 -10.000000} {-10.000000 -10.000000 10.000000} style solid width 4
-graphics top line {10.000000 -10.000000 -10.000000} {10.000000 -10.000000 10.000000} style solid width 4
-graphics top line {-10.000000 10.000000 -10.000000} {10.000000 10.000000 -10.000000} style solid width 4
-graphics top line {-10.000000 -10.000000 10.000000} {-10.000000 10.000000 10.000000} style solid width 4
-graphics top line {10.000000 -10.000000 -10.000000} {10.000000 10.000000 -10.000000} style solid width 4
-graphics top line {-10.000000 10.000000 -10.000000} {-10.000000 10.000000 10.000000} style solid width 4
-graphics top line {-10.000000 -10.000000 10.000000} {10.000000 -10.000000 10.000000} style solid width 4
-graphics top line {10.000000 10.000000 10.000000} {10.000000 10.000000 -10.000000} style solid width 4
-graphics top line {10.000000 10.000000 10.000000} {10.000000 -10.000000 10.000000} style solid width 4
-graphics top line {10.000000 10.000000 10.000000} {-10.000000 10.000000 10.000000} style solid width 4
-mol delrep 0 top
-mol representation VDW 0.900000 42.000000
-mol color Name
-mol selection {all}
-mol material Opaque
-mol addrep top
-mol selupdate 0 top 0
-mol colupdate 0 top 0
-mol scaleminmax top 0 0.000000 0.000000
-mol smoothrep top 0 0
-mol drawframes top 0 {now}
-mol clipplane center 0 0 top {0.0 0.0 0.0}
-mol clipplane color  0 0 top {0.5 0.5 0.5 }
-mol clipplane normal 0 0 top {0.0 0.0 1.0}
-mol clipplane status 0 0 top {0}
-mol clipplane center 1 0 top {0.0 0.0 0.0}
-mol clipplane color  1 0 top {0.5 0.5 0.5 }
-mol clipplane normal 1 0 top {0.0 0.0 1.0}
-mol clipplane status 1 0 top {0}
-mol clipplane center 2 0 top {0.0 0.0 0.0}
-mol clipplane color  2 0 top {0.5 0.5 0.5 }
-mol clipplane normal 2 0 top {0.0 0.0 1.0}
-mol clipplane status 2 0 top {0}
-mol clipplane center 3 0 top {0.0 0.0 0.0}
-mol clipplane color  3 0 top {0.5 0.5 0.5 }
-mol clipplane normal 3 0 top {0.0 0.0 1.0}
-mol clipplane status 3 0 top {0}
-mol clipplane center 4 0 top {0.0 0.0 0.0}
-mol clipplane color  4 0 top {0.5 0.5 0.5 }
-mol clipplane normal 4 0 top {0.0 0.0 1.0}
-mol clipplane status 4 0 top {0}
-mol clipplane center 5 0 top {0.0 0.0 0.0}
-mol clipplane color  5 0 top {0.5 0.5 0.5 }
-mol clipplane normal 5 0 top {0.0 0.0 1.0}
-mol clipplane status 5 0 top {0}
-mol rename top dump.mc.lammpstrj
-set viewpoints([molinfo top]) {{{1 0 0 -0.02154} {0 1 0 -0.331865} {0 0 1 -0.22858} {0 0 0 1}} {{1 0 0 0} {0 1.00583e-07 1 0} {0 -1 1.00583e-07 0} {0 0 0 1}} {{0.0627353 0 0 0} {0 0.0627353 0 0} {0 0 0.0627353 0} {0 0 0 1}} {{1 0 0 0} {0 1 0 0} {0 0 1 0} {0 0 0 1}}}
-lappend viewplist [molinfo top]
-set topmol [molinfo top]
-# done with molecule 0
-foreach v $viewplist {
-  molinfo $v set {center_matrix rotate_matrix scale_matrix global_matrix} $viewpoints($v)
-}
-foreach v $fixedlist {
-  molinfo $v set fixed 1
-}
-unset viewplist
-unset fixedlist
-mol top $topmol
-unset topmol
-proc vmdrestoremycolors {} {
-color scale colors RWB {1.0 0.0 0.0} {1.0 1.0 1.0} {0.0 0.0 1.0}
-color scale colors BWR {0.0 0.0 1.0} {1.0 1.0 1.0} {1.0 0.0 0.0}
-color scale colors RGryB {1.0 0.0 0.0} {0.5 0.5 0.5} {0.0 0.0 1.0}
-color scale colors BGryR {0.0 0.0 1.0} {0.5 0.5 0.5} {1.0 0.0 0.0}
-color scale colors RGB {1.0 0.0 0.0} {0.0 1.0 0.0} {0.0 0.0 1.0}
-color scale colors BGR {0.0 0.0 1.0} {0.0 1.0 0.0} {1.0 0.0 0.0}
-color scale colors RWG {1.0 0.0 0.0} {1.0 1.0 1.0} {0.0 1.0 0.0}
-color scale colors GWR {0.0 1.0 0.0} {1.0 1.0 1.0} {1.0 0.0 0.0}
-color scale colors GWB {0.0 1.0 0.0} {1.0 1.0 1.0} {0.0 0.0 1.0}
-color scale colors BWG {0.0 0.0 1.0} {1.0 1.0 1.0} {0.0 1.0 0.0}
-color scale colors BlkW {0.0 0.0 0.0} {0.5 0.5 0.5} {1.0 1.0 1.0}
-color scale colors WBlk {1.0 1.0 1.0} {0.5 0.5 0.5} {0.0 0.0 0.0}
-color scale colors cividis {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors viridis {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors magma {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors plasma {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors inferno {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L3 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L8 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L9 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L16 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L17 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L18 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L19 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_L20 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_C2 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_C4 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_C6 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_C7 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_I1 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_I2 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_I3 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_D11 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_D12 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors turbo {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-color scale colors CET_R2 {0.0 0.0 0.0} {0.0 0.0 0.0} {0.0 0.0 0.0}
-  color scale method RWB
-  set colorcmds {
-    {color Display {BackgroundTop} black}
-    {color Display {BackgroundBot} blue2}
-    {color Display {FPS} white}
-    {color Name {LPA} green}
-    {color Name {LPB} green}
-    {color Name {1} pink}
-    {color Type {LP} green}
-    {color Type {DRUD} pink}
-    {color Type {1} pink}
-    {color Element {X} cyan}
-    {color Element {Ac} ochre}
-    {color Element {Ag} ochre}
-    {color Element {Al} ochre}
-    {color Element {Am} ochre}
-    {color Element {Ar} ochre}
-    {color Element {As} ochre}
-    {color Element {At} ochre}
-    {color Element {Au} ochre}
-    {color Element {B} ochre}
-    {color Element {Ba} ochre}
-    {color Element {Be} ochre}
-    {color Element {Bh} ochre}
-    {color Element {Bi} ochre}
-    {color Element {Bk} ochre}
-    {color Element {Br} ochre}
-    {color Element {Ca} ochre}
-    {color Element {Cd} ochre}
-    {color Element {Ce} ochre}
-    {color Element {Cf} ochre}
-    {color Element {Cl} ochre}
-    {color Element {Cm} ochre}
-    {color Element {Co} ochre}
-    {color Element {Cr} ochre}
-    {color Element {Cs} ochre}
-    {color Element {Cu} ochre}
-    {color Element {Db} ochre}
-    {color Element {Ds} ochre}
-    {color Element {Dy} ochre}
-    {color Element {Er} ochre}
-    {color Element {Es} ochre}
-    {color Element {Eu} ochre}
-    {color Element {F} ochre}
-    {color Element {Fe} ochre}
-    {color Element {Fm} ochre}
-    {color Element {Fr} ochre}
-    {color Element {Ga} ochre}
-    {color Element {Gd} ochre}
-    {color Element {Ge} ochre}
-    {color Element {He} ochre}
-    {color Element {Hf} ochre}
-    {color Element {Hg} ochre}
-    {color Element {Ho} ochre}
-    {color Element {Hs} ochre}
-    {color Element {I} ochre}
-    {color Element {In} ochre}
-    {color Element {Ir} ochre}
-    {color Element {K} ochre}
-    {color Element {Kr} ochre}
-    {color Element {La} ochre}
-    {color Element {Li} ochre}
-    {color Element {Lr} ochre}
-    {color Element {Lu} ochre}
-    {color Element {Md} ochre}
-    {color Element {Mg} ochre}
-    {color Element {Mn} ochre}
-    {color Element {Mo} ochre}
-    {color Element {Mt} ochre}
-    {color Element {Na} ochre}
-    {color Element {Nb} ochre}
-    {color Element {Nd} ochre}
-    {color Element {Ne} ochre}
-    {color Element {Ni} ochre}
-    {color Element {No} ochre}
-    {color Element {Np} ochre}
-    {color Element {Os} ochre}
-    {color Element {Pa} ochre}
-    {color Element {Pb} ochre}
-    {color Element {Pd} ochre}
-    {color Element {Pm} ochre}
-    {color Element {Po} ochre}
-    {color Element {Pr} ochre}
-    {color Element {Pt} ochre}
-    {color Element {Pu} ochre}
-    {color Element {Ra} ochre}
-    {color Element {Rb} ochre}
-    {color Element {Re} ochre}
-    {color Element {Rf} ochre}
-    {color Element {Rg} ochre}
-    {color Element {Rh} ochre}
-    {color Element {Rn} ochre}
-    {color Element {Ru} ochre}
-    {color Element {Sb} ochre}
-    {color Element {Sc} ochre}
-    {color Element {Se} ochre}
-    {color Element {Sg} ochre}
-    {color Element {Si} ochre}
-    {color Element {Sm} ochre}
-    {color Element {Sn} ochre}
-    {color Element {Sr} ochre}
-    {color Element {Ta} ochre}
-    {color Element {Tb} ochre}
-    {color Element {Tc} ochre}
-    {color Element {Te} ochre}
-    {color Element {Th} ochre}
-    {color Element {Ti} ochre}
-    {color Element {Tl} ochre}
-    {color Element {Tm} ochre}
-    {color Element {U} ochre}
-    {color Element {V} ochre}
-    {color Element {W} ochre}
-    {color Element {Xe} ochre}
-    {color Element {Y} ochre}
-    {color Element {Yb} ochre}
-    {color Element {Zr} ochre}
-    {color Resname {UNK} silver}
-    {color Chain {X} blue}
-    {color Segname {} blue}
-    {color Conformation {all} blue}
-    {color Molecule {0} blue}
-    {color Molecule {dump.mc.lammpstrj} red}
-    {color Structure {3_10_Helix} blue}
-    {color Surface {Grasp} gray}
-    {color Labels {Springs} orange}
-    {color Stage {Even} gray}
-    {color Stage {Odd} silver}
-  }
-  foreach colcmd $colorcmds {
-    set val [catch {eval $colcmd}]
-  }
-  color change rgb 0 0.47679975628852844 0.4797555208206177 0.5373134613037109
-  color change rgb 2 0.3499999940395355 0.3499999940395355 0.3499999940395355
-  color change rgb 3 1.0 0.5 0.0
-  color change rgb 4 1.0 1.0 0.0
-  color change rgb 5 0.5 0.5 0.20000000298023224
-  color change rgb 6 0.6000000238418579 0.6000000238418579 0.6000000238418579
-  color change rgb 7 0.0 1.0 0.0
-  color change rgb 9 0.0 1.100000023841858 1.100000023841858
-  color change rgb 11 0.6499999761581421 0.0 0.6499999761581421
-  color change rgb 12 0.5 0.8999999761581421 0.4000000059604645
-  color change rgb 13 0.8999999761581421 0.4000000059604645 0.699999988079071
-  color change rgb 14 0.5 0.30000001192092896 0.0
-  color change rgb 15 0.5 0.5 0.75
-  color change rgb 17 0.8799999952316284 0.9700000286102295 0.019999999552965164
-  color change rgb 18 0.550000011920929 0.8999999761581421 0.019999999552965164
-  color change rgb 19 0.0 0.8999999761581421 0.03999999910593033
-  color change rgb 20 0.0 0.8999999761581421 0.5
-  color change rgb 21 0.0 0.8799999952316284 1.0
-  color change rgb 22 0.0 0.7599999904632568 1.0
-  color change rgb 23 0.019999999552965164 0.3799999952316284 0.6700000166893005
-  color change rgb 24 0.009999999776482582 0.03999999910593033 0.9300000071525574
-  color change rgb 25 0.27000001072883606 0.0 0.9800000190734863
-  color change rgb 26 0.44999998807907104 0.0 0.8999999761581421
-  color change rgb 27 0.8999999761581421 0.0 0.8999999761581421
-  color change rgb 28 1.0 0.0 0.6600000262260437
-  color change rgb 29 0.9800000190734863 0.0 0.23000000417232513
-  color change rgb 30 0.8100000023841858 0.0 0.0
-  color change rgb 31 0.8899999856948853 0.3499999940395355 0.0
-  color change rgb 32 0.9599999785423279 0.7200000286102295 0.0
-}
-vmdrestoremycolors
-label textsize 1.0
diff --git a/tests/PARM.lammps b/tests/PARM.lammps
deleted file mode 100644
index cc750d7..0000000
--- a/tests/PARM.lammps
+++ /dev/null
@@ -1,8 +0,0 @@
-# LAMMPS parameter file 
-
-mass 1 1.0
-mass 2 1.0
-
-pair_coeff 1 1 0.1 3.0
-pair_coeff 2 2 1.0 6.0
-
diff --git a/tests/final.data b/tests/final.data
deleted file mode 100644
index b483b00..0000000
--- a/tests/final.data
+++ /dev/null
@@ -1,1014 +0,0 @@
-# LAMMPS data file 
-
-500 atoms
-2 atom types
-
--1240092.163 1240092.163 xlo xhi
--1240092.163 1240092.163 ylo yhi
--1240092.163 1240092.163 zlo zhi
-
-Atoms
-
-1 1 1 0.000 -435037.392 -260248.033 -885098.641 
-2 1 1 0.000 275533.660 -1063181.594 -1208708.201 
-3 1 1 0.000 -384878.633 965907.147 261865.227 
-4 1 1 0.000 670447.543 1092468.894 576513.195 
-5 1 1 0.000 -58941.881 -23327.298 474532.789 
-6 1 1 0.000 -1196457.188 533348.912 1171141.361 
-7 1 1 0.000 362769.538 -167362.480 -538805.508 
-8 1 1 0.000 726362.108 708079.564 -953322.133 
-9 1 1 0.000 -543944.360 -625277.462 -869283.882 
-10 1 1 0.000 222522.265 758456.017 -258208.008 
-11 1 1 0.000 -181914.630 -279070.892 331331.876 
-12 1 1 0.000 719175.891 -214895.431 678241.227 
-13 1 1 0.000 -882377.908 -505500.132 -710447.163 
-14 1 1 0.000 -681969.340 927624.272 -1183065.340 
-15 1 1 0.000 927574.805 771197.136 -121147.512 
-16 1 1 0.000 -376338.952 -213742.207 -993112.685 
-17 1 1 0.000 665456.511 334042.845 54249.578 
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-302 -0.002 0.009 -0.001 
-303 -0.018 0.000 0.008 
-304 -0.012 -0.019 0.006 
-305 -0.005 -0.003 -0.008 
-306 0.003 0.003 0.003 
-307 0.017 0.013 -0.004 
-308 -0.001 -0.002 0.001 
-309 0.004 0.005 0.011 
-310 0.010 -0.004 0.006 
-311 0.000 0.000 0.021 
-312 0.004 -0.005 0.003 
-313 -0.019 -0.009 0.014 
-314 -0.016 0.001 0.005 
-315 0.004 -0.010 0.010 
-316 0.002 0.015 0.010 
-317 -0.004 0.002 -0.004 
-318 0.020 0.001 0.001 
-319 -0.014 0.001 0.004 
-320 0.005 0.014 -0.007 
-321 0.005 0.004 -0.009 
-322 -0.002 0.011 -0.003 
-323 -0.006 -0.016 0.005 
-324 0.008 -0.009 0.001 
-325 0.010 -0.021 -0.006 
-326 -0.021 -0.011 0.001 
-327 -0.011 -0.002 0.006 
-328 -0.004 0.012 0.001 
-329 0.014 0.006 0.004 
-330 0.001 0.000 0.014 
-331 -0.010 0.003 -0.012 
-332 0.005 -0.008 -0.001 
-333 0.000 -0.001 -0.007 
-334 -0.001 -0.010 0.012 
-335 0.003 -0.008 0.014 
-336 0.006 -0.010 -0.009 
-337 -0.001 -0.004 0.008 
-338 -0.011 0.012 -0.001 
-339 0.018 0.008 -0.005 
-340 0.003 0.010 0.009 
-341 0.004 -0.012 0.002 
-342 -0.017 0.000 0.015 
-343 -0.004 0.001 0.012 
-344 -0.007 0.006 0.005 
-345 -0.006 0.003 -0.009 
-346 0.004 -0.005 0.014 
-347 -0.004 0.003 0.008 
-348 0.016 0.002 0.004 
-349 0.005 0.009 -0.007 
-350 0.005 -0.006 0.005 
-351 0.008 0.003 -0.012 
-352 -0.016 0.011 -0.005 
-353 0.004 0.010 0.000 
-354 0.007 -0.000 0.010 
-355 -0.022 0.004 -0.015 
-356 0.009 0.022 0.006 
-357 -0.001 0.008 0.004 
-358 -0.016 -0.004 0.000 
-359 108291.396 55574.317 -115480.101 
-360 0.000 0.004 -0.020 
-361 0.006 -0.000 -0.003 
-362 -0.000 0.000 0.009 
-363 0.000 0.001 0.003 
-364 0.002 -0.009 -0.001 
-365 -0.009 0.002 0.001 
-366 -0.010 -0.006 -0.006 
-367 -0.002 -0.001 -0.006 
-368 -0.003 0.003 -0.001 
-369 0.001 0.008 0.001 
-370 0.009 0.009 0.002 
-371 0.005 0.004 0.012 
-372 -0.004 0.009 -0.014 
-373 0.015 0.004 0.011 
-374 0.008 0.010 -0.009 
-375 -0.008 -0.002 -0.006 
-376 -0.002 -0.007 -0.004 
-377 0.012 0.003 0.004 
-378 -0.002 0.001 -0.006 
-379 -0.006 -0.013 0.007 
-380 -0.011 -0.004 0.007 
-381 0.003 -0.012 -0.005 
-382 -0.005 0.001 0.001 
-383 -0.004 0.001 0.005 
-384 -0.016 -0.007 0.004 
-385 -0.006 -0.006 0.013 
-386 -0.001 0.002 0.013 
-387 0.013 0.005 0.004 
-388 0.007 0.002 -0.015 
-389 0.020 0.004 -0.014 
-390 0.003 -0.008 -0.005 
-391 0.011 -0.011 -0.020 
-392 0.017 -0.012 -0.002 
-393 0.006 -0.003 0.014 
-394 0.005 0.006 0.000 
-395 -0.012 -0.004 0.004 
-396 -0.020 -0.004 0.007 
-397 -0.004 0.013 -0.003 
-398 -0.001 -0.015 0.001 
-399 -0.004 0.005 0.004 
-400 0.009 -0.012 0.009 
-401 0.006 0.001 -0.006 
-402 -0.010 -0.004 -0.009 
-403 -0.008 -0.007 0.012 
-404 0.000 0.005 0.001 
-405 -0.005 0.013 -0.008 
-406 -0.023 -0.008 -0.013 
-407 0.011 0.009 -0.015 
-408 0.005 0.007 0.007 
-409 0.000 -0.001 0.006 
-410 0.003 0.007 -0.003 
-411 -0.003 0.016 0.012 
-412 -0.006 -0.005 -0.012 
-413 0.014 -0.010 -0.001 
-414 0.001 -0.006 -0.010 
-415 -0.007 0.015 -0.002 
-416 0.012 -0.016 -0.002 
-417 0.015 0.005 0.011 
-418 0.002 0.002 -0.017 
-419 0.002 0.006 -0.016 
-420 0.004 0.007 -0.026 
-421 -0.003 -0.016 -0.004 
-422 -0.002 -0.000 0.021 
-423 0.004 -0.013 0.004 
-424 0.002 -0.014 0.007 
-425 -0.002 0.001 0.008 
-426 -0.013 -0.018 -0.001 
-427 0.012 0.008 0.026 
-428 0.007 0.007 0.009 
-429 0.014 0.009 -0.011 
-430 0.006 0.009 -0.002 
-431 0.002 0.012 0.011 
-432 -0.004 0.001 0.002 
-433 -0.001 0.008 -0.006 
-434 0.004 -0.003 -0.008 
-435 -0.006 -0.015 -0.013 
-436 -0.019 0.014 -0.003 
-437 0.005 0.001 0.002 
-438 0.001 0.000 -0.006 
-439 0.000 0.000 -0.001 
-440 -0.004 0.007 -0.005 
-441 -0.006 -0.007 0.008 
-442 0.002 -0.009 0.002 
-443 -0.005 0.002 0.014 
-444 -0.002 -0.004 0.007 
-445 0.000 -0.005 -0.009 
-446 0.019 0.009 -0.001 
-447 0.010 0.004 -0.002 
-448 0.005 0.002 -0.010 
-449 -0.003 -0.008 0.004 
-450 0.006 0.013 -0.007 
-451 -0.009 -0.009 -0.009 
-452 0.026 -0.008 0.010 
-453 -0.007 -0.011 -0.012 
-454 -0.012 -0.009 0.007 
-455 -0.012 0.016 -0.001 
-456 -0.002 -0.005 -0.009 
-457 -0.008 0.009 0.012 
-458 -0.006 0.002 -0.000 
-459 -0.006 -0.004 -0.011 
-460 -0.016 -0.002 -0.009 
-461 -0.007 0.004 -0.003 
-462 -0.002 -0.008 0.004 
-463 0.008 -0.009 0.012 
-464 0.004 -0.019 0.008 
-465 0.002 -0.000 -0.006 
-466 0.002 0.008 0.003 
-467 0.006 -0.010 0.003 
-468 -0.011 0.001 0.028 
-469 0.002 -0.002 -0.006 
-470 0.012 0.002 -0.018 
-471 0.009 0.003 -0.014 
-472 -0.008 -0.018 -0.003 
-473 -0.013 0.003 0.009 
-474 -0.003 0.005 -0.019 
-475 0.001 -0.000 0.008 
-476 -0.007 -0.011 -0.005 
-477 -0.013 -0.005 0.001 
-478 -0.008 0.010 -0.001 
-479 -0.001 -0.017 -0.008 
-480 -0.006 -0.013 -0.003 
-481 0.012 -0.003 -0.018 
-482 0.002 -0.004 -0.005 
-483 -0.004 0.002 -0.007 
-484 0.006 0.004 -0.004 
-485 0.011 0.021 -0.004 
-486 0.004 0.002 -0.002 
-487 0.004 0.011 0.005 
-488 0.007 0.010 -0.009 
-489 -0.016 -0.006 0.004 
-490 -0.008 0.011 -0.005 
-491 0.014 -0.001 -0.006 
-492 -0.006 -0.015 0.003 
-493 0.000 0.015 0.009 
-494 -0.003 -0.008 -0.007 
-495 0.010 0.000 -0.007 
-496 0.010 0.011 0.012 
-497 0.010 0.001 0.002 
-498 -0.009 0.001 0.015 
-499 0.001 0.006 0.011 
-500 -0.003 0.011 0.006 
diff --git a/tests/initial.data b/tests/initial.data
deleted file mode 100644
index 7a63ae9..0000000
--- a/tests/initial.data
+++ /dev/null
@@ -1,1014 +0,0 @@
-# LAMMPS data file 
-
-500 atoms
-2 atom types
-
--250.000 250.000 xlo xhi
--250.000 250.000 ylo yhi
--250.000 250.000 zlo zhi
-
-Atoms
-
-1 1 1 0.000 -87.701 -52.476 -178.433 
-2 1 1 0.000 55.532 -214.349 -243.676 
-3 1 1 0.000 -77.598 194.724 52.797 
-4 1 1 0.000 135.153 220.240 116.215 
-5 1 1 0.000 -11.879 -4.707 95.665 
-6 1 1 0.000 -241.197 107.531 236.102 
-7 1 1 0.000 73.135 -33.747 -108.631 
-8 1 1 0.000 146.431 142.752 -192.198 
-9 1 1 0.000 -109.660 -126.064 -175.248 
-10 1 1 0.000 44.867 152.901 -52.053 
-11 1 1 0.000 -36.689 -56.264 66.793 
-12 1 1 0.000 144.974 -43.316 136.731 
-13 1 1 0.000 -177.890 -101.908 -143.224 
-14 1 1 0.000 -137.482 187.011 -238.508 
-15 1 1 0.000 186.993 155.463 -24.422 
-16 1 1 0.000 -75.877 -43.088 -200.207 
-17 1 1 0.000 134.147 67.345 10.946 
-18 1 1 0.000 94.327 -239.769 116.898 
-19 1 1 0.000 110.376 28.108 88.716 
-20 1 1 0.000 202.763 -9.955 -217.052 
-21 1 1 0.000 -71.994 -138.941 248.268 
-22 1 1 0.000 146.967 63.721 182.026 
-23 1 1 0.000 -19.807 -225.220 62.524 
-24 1 1 0.000 -114.730 201.132 -184.325 
-25 1 1 0.000 75.654 190.841 26.219 
-26 1 1 0.000 -105.992 -114.992 59.149 
-27 1 1 0.000 103.501 179.390 -14.156 
-28 1 1 0.000 133.280 37.360 -132.623 
-29 1 1 0.000 105.694 -113.296 144.757 
-30 1 1 0.000 107.591 -26.133 -242.375 
-31 1 1 0.000 -248.845 149.062 -181.903 
-32 1 1 0.000 132.029 -192.183 -45.348 
-33 1 1 0.000 83.800 70.191 200.908 
-34 1 1 0.000 -101.289 12.349 -156.365 
-35 1 1 0.000 170.060 -156.896 -86.858 
-36 1 1 0.000 140.489 164.374 98.895 
-37 1 1 0.000 189.010 -113.179 40.118 
-38 1 1 0.000 -127.394 -17.435 143.950 
-39 1 1 0.000 -163.939 59.760 -22.084 
-40 1 1 0.000 -196.441 93.447 231.414 
-41 1 1 0.000 143.749 -75.411 -82.665 
-42 1 1 0.000 144.047 212.569 -159.106 
-43 1 1 0.000 183.717 188.827 -185.932 
-44 1 1 0.000 14.066 30.580 105.543 
-45 1 1 0.000 110.712 238.620 164.779 
-46 1 1 0.000 52.539 187.476 18.009 
-47 1 1 0.000 -190.475 -77.329 -247.777 
-48 1 1 0.000 4.890 -30.200 -167.495 
-49 1 1 0.000 -200.440 -109.588 126.000 
-50 1 1 0.000 128.143 67.464 -146.250 
-51 1 1 0.000 -180.434 -25.880 -168.757 
-52 1 1 0.000 -203.230 186.578 -35.471 
-53 1 1 0.000 -106.219 -237.011 157.686 
-54 1 1 0.000 194.288 -91.707 101.345 
-55 1 1 0.000 -66.424 -99.974 -140.868 
-56 1 1 0.000 -205.280 107.301 -84.241 
-57 1 1 0.000 -28.102 -234.731 -122.807 
-58 1 1 0.000 95.124 73.641 65.510 
-59 1 1 0.000 -149.331 -106.377 120.103 
-60 1 1 0.000 147.512 -50.116 210.145 
-61 1 1 0.000 126.568 193.332 195.805 
-62 1 1 0.000 -105.446 -30.173 102.275 
-63 1 1 0.000 174.681 -94.384 -149.620 
-64 1 1 0.000 98.583 -236.581 52.248 
-65 1 1 0.000 202.588 63.608 10.828 
-66 1 1 0.000 147.420 107.403 48.632 
-67 1 1 0.000 -85.301 -38.370 -176.295 
-68 1 1 0.000 45.967 68.774 -160.986 
-69 1 1 0.000 -217.747 186.044 -76.690 
-70 1 1 0.000 -62.001 96.952 116.530 
-71 1 1 0.000 -164.691 -160.492 -68.635 
-72 1 1 0.000 135.437 -196.633 -120.670 
-73 1 1 0.000 248.237 102.818 -213.678 
-74 1 1 0.000 191.329 76.119 78.126 
-75 1 1 0.000 35.381 -111.011 -236.753 
-76 1 1 0.000 129.235 -76.614 190.699 
-77 1 1 0.000 86.054 34.052 148.620 
-78 1 1 0.000 -115.548 188.636 82.284 
-79 1 1 0.000 246.199 -198.321 -67.818 
-80 1 1 0.000 -26.098 -216.952 104.823 
-81 1 1 0.000 -232.686 23.744 -50.193 
-82 1 1 0.000 -241.892 -200.331 -76.045 
-83 1 1 0.000 75.598 246.123 -153.020 
-84 1 1 0.000 -101.520 67.769 -156.651 
-85 1 1 0.000 223.854 21.685 -248.342 
-86 1 1 0.000 -110.769 -61.302 68.794 
-87 1 1 0.000 249.636 10.384 -248.875 
-88 1 1 0.000 116.746 50.426 -152.141 
-89 1 1 0.000 -45.391 234.088 -166.887 
-90 1 1 0.000 -131.242 -197.918 -87.741 
-91 1 1 0.000 112.792 -61.840 -93.443 
-92 1 1 0.000 -18.112 97.010 147.426 
-93 1 1 0.000 67.666 -31.764 -172.248 
-94 1 1 0.000 -162.940 155.780 240.666 
-95 1 1 0.000 -217.287 241.467 196.730 
-96 1 1 0.000 247.150 38.829 -186.049 
-97 1 1 0.000 76.889 36.593 -156.602 
-98 1 1 0.000 83.535 139.595 137.295 
-99 1 1 0.000 -83.316 10.532 186.734 
-100 1 1 0.000 -178.020 83.574 163.846 
-101 1 2 0.000 -24.121 183.959 83.778 
-102 1 2 0.000 78.072 26.624 69.886 
-103 1 2 0.000 228.657 -3.071 -141.226 
-104 1 2 0.000 -141.574 -225.312 194.070 
-105 1 2 0.000 69.323 37.136 -173.745 
-106 1 2 0.000 184.152 -56.252 112.513 
-107 1 2 0.000 169.606 118.491 -228.990 
-108 1 2 0.000 -249.358 -94.591 136.068 
-109 1 2 0.000 249.313 -99.843 -155.496 
-110 1 2 0.000 -91.189 -162.352 35.599 
-111 1 2 0.000 124.241 -65.344 -142.479 
-112 1 2 0.000 -133.116 236.940 -101.306 
-113 1 2 0.000 -220.903 144.595 -98.769 
-114 1 2 0.000 -138.519 -238.510 -28.950 
-115 1 2 0.000 232.662 224.164 -97.889 
-116 1 2 0.000 -140.174 -117.579 114.990 
-117 1 2 0.000 240.947 107.306 95.726 
-118 1 2 0.000 -85.149 -50.324 237.731 
-119 1 2 0.000 132.486 -36.673 123.858 
-120 1 2 0.000 -113.259 -223.307 13.774 
-121 1 2 0.000 -197.258 98.174 -12.094 
-122 1 2 0.000 74.705 -56.528 170.460 
-123 1 2 0.000 -156.962 107.744 -172.081 
-124 1 2 0.000 -140.501 -195.942 209.930 
-125 1 2 0.000 -155.833 -230.940 184.309 
-126 1 2 0.000 -53.160 90.859 -61.678 
-127 1 2 0.000 166.443 226.710 197.574 
-128 1 2 0.000 -246.110 -202.769 148.209 
-129 1 2 0.000 -123.831 -139.236 -80.079 
-130 1 2 0.000 -145.040 8.931 38.842 
-131 1 2 0.000 4.740 -53.398 39.608 
-132 1 2 0.000 -153.504 146.650 155.006 
-133 1 2 0.000 -140.275 241.857 -143.877 
-134 1 2 0.000 -134.791 200.144 103.806 
-135 1 2 0.000 81.065 -133.837 -227.730 
-136 1 2 0.000 -102.317 59.941 184.463 
-137 1 2 0.000 -44.006 0.958 -47.486 
-138 1 2 0.000 146.618 41.755 -53.078 
-139 1 2 0.000 -105.485 -88.962 -240.421 
-140 1 2 0.000 72.251 -83.802 -185.143 
-141 1 2 0.000 207.462 -130.254 -213.640 
-142 1 2 0.000 -190.297 -226.256 -52.890 
-143 1 2 0.000 95.394 87.032 -123.258 
-144 1 2 0.000 52.423 -7.393 -228.757 
-145 1 2 0.000 182.883 -158.427 -60.905 
-146 1 2 0.000 238.208 -191.917 -188.619 
-147 1 2 0.000 0.488 203.173 249.335 
-148 1 2 0.000 221.038 158.390 167.610 
-149 1 2 0.000 116.509 61.290 179.646 
-150 1 2 0.000 151.720 56.349 -85.857 
-151 1 2 0.000 50.467 -232.714 226.199 
-152 1 2 0.000 73.082 -10.750 199.916 
-153 1 2 0.000 105.336 26.472 184.066 
-154 1 2 0.000 219.479 214.057 100.168 
-155 1 2 0.000 76.068 -166.919 145.020 
-156 1 2 0.000 176.756 -122.573 -126.665 
-157 1 2 0.000 -222.308 48.884 45.582 
-158 1 2 0.000 245.705 227.489 164.723 
-159 1 2 0.000 24.846 94.383 188.083 
-160 1 2 0.000 51.447 -246.608 -25.916 
-161 1 2 0.000 0.844 80.984 104.800 
-162 1 2 0.000 92.527 150.709 -168.445 
-163 1 2 0.000 181.141 -90.667 -71.023 
-164 1 2 0.000 -83.469 -209.322 31.008 
-165 1 2 0.000 -185.511 121.452 -33.450 
-166 1 2 0.000 -107.339 -97.535 -195.191 
-167 1 2 0.000 86.753 19.937 90.965 
-168 1 2 0.000 -188.115 -68.163 -23.781 
-169 1 2 0.000 -95.545 19.171 -212.829 
-170 1 2 0.000 -222.774 105.444 -201.839 
-171 1 2 0.000 -88.181 220.964 31.054 
-172 1 2 0.000 173.580 -134.929 187.861 
-173 1 2 0.000 -8.593 45.027 -130.512 
-174 1 2 0.000 206.476 52.775 -87.002 
-175 1 2 0.000 41.755 -83.817 63.561 
-176 1 2 0.000 201.226 -49.554 184.922 
-177 1 2 0.000 -222.362 -144.748 -1.058 
-178 1 2 0.000 248.506 4.719 180.574 
-179 1 2 0.000 147.318 244.124 -55.352 
-180 1 2 0.000 -107.752 186.551 41.095 
-181 1 2 0.000 211.412 17.651 122.128 
-182 1 2 0.000 -205.259 -137.779 78.109 
-183 1 2 0.000 -241.076 107.955 -70.050 
-184 1 2 0.000 212.787 38.939 223.806 
-185 1 2 0.000 -193.038 187.817 143.630 
-186 1 2 0.000 46.331 110.852 204.345 
-187 1 2 0.000 34.169 137.393 170.060 
-188 1 2 0.000 -28.068 68.668 -15.874 
-189 1 2 0.000 82.134 141.051 23.631 
-190 1 2 0.000 55.949 -120.854 187.778 
-191 1 2 0.000 0.991 196.531 -171.624 
-192 1 2 0.000 -247.701 226.350 -59.141 
-193 1 2 0.000 93.828 219.579 -143.102 
-194 1 2 0.000 143.063 38.791 -11.728 
-195 1 2 0.000 -214.854 168.942 193.309 
-196 1 2 0.000 -8.882 -187.512 56.106 
-197 1 2 0.000 -176.117 81.820 -82.976 
-198 1 2 0.000 -24.568 95.910 -230.492 
-199 1 2 0.000 198.693 32.490 239.792 
-200 1 2 0.000 177.111 -21.684 -141.681 
-201 1 2 0.000 -121.925 140.743 -10.718 
-202 1 2 0.000 -102.525 -34.185 55.923 
-203 1 2 0.000 139.303 136.456 -200.069 
-204 1 2 0.000 47.987 51.733 -23.992 
-205 1 2 0.000 42.609 233.335 -248.717 
-206 1 2 0.000 -153.296 241.545 -235.552 
-207 1 2 0.000 -148.577 38.579 -158.313 
-208 1 2 0.000 -231.442 -85.788 98.277 
-209 1 2 0.000 78.960 168.954 161.425 
-210 1 2 0.000 97.035 -242.831 -192.488 
-211 1 2 0.000 124.725 40.487 61.617 
-212 1 2 0.000 198.899 242.162 34.196 
-213 1 2 0.000 -18.615 166.746 168.767 
-214 1 2 0.000 -126.361 162.652 230.702 
-215 1 2 0.000 -206.416 -104.719 -17.502 
-216 1 2 0.000 27.903 82.315 -208.984 
-217 1 2 0.000 9.229 1.343 -5.116 
-218 1 2 0.000 208.728 15.000 -196.867 
-219 1 2 0.000 55.421 -23.156 226.626 
-220 1 2 0.000 -189.566 -137.530 -78.331 
-221 1 2 0.000 -234.501 17.249 -4.121 
-222 1 2 0.000 156.686 188.438 11.267 
-223 1 2 0.000 -130.967 16.625 96.049 
-224 1 2 0.000 -184.007 -125.634 35.917 
-225 1 2 0.000 -77.872 226.534 -37.052 
-226 1 2 0.000 -135.600 78.899 -214.672 
-227 1 2 0.000 82.978 231.699 73.202 
-228 1 2 0.000 -115.077 -160.581 -143.543 
-229 1 2 0.000 185.773 217.239 224.390 
-230 1 2 0.000 -106.149 132.302 -163.939 
-231 1 2 0.000 234.005 -198.059 242.931 
-232 1 2 0.000 62.968 -50.638 80.085 
-233 1 2 0.000 -3.999 129.419 -162.908 
-234 1 2 0.000 62.520 -34.177 -183.204 
-235 1 2 0.000 -169.674 212.220 -133.027 
-236 1 2 0.000 -37.727 17.991 90.232 
-237 1 2 0.000 239.603 58.736 231.128 
-238 1 2 0.000 -152.586 8.847 219.549 
-239 1 2 0.000 -132.778 -9.680 90.773 
-240 1 2 0.000 -135.451 -162.052 -9.468 
-241 1 2 0.000 -148.480 -145.261 -42.873 
-242 1 2 0.000 19.067 176.976 237.233 
-243 1 2 0.000 -65.102 122.687 172.010 
-244 1 2 0.000 -153.400 24.210 -0.107 
-245 1 2 0.000 -209.270 -149.359 23.245 
-246 1 2 0.000 -51.003 102.324 -208.187 
-247 1 2 0.000 180.177 -117.814 -61.778 
-248 1 2 0.000 215.177 -155.562 143.978 
-249 1 2 0.000 -35.629 -194.319 -66.636 
-250 1 2 0.000 -228.079 141.920 245.124 
-251 1 2 0.000 102.511 200.088 -158.563 
-252 1 2 0.000 -168.826 -142.913 72.373 
-253 1 2 0.000 -235.463 3.255 -214.200 
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diff --git a/tests/initialize/test.ipynb b/tests/initialize/test.ipynb
deleted file mode 100644
index 44b21ca..0000000
--- a/tests/initialize/test.ipynb
+++ /dev/null
@@ -1,62 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Atom positions:\n",
-      "[[-1.15270975  1.25033545  0.39460297]\n",
-      " [ 2.10225087 -2.12285757 -2.43760443]\n",
-      " [ 0.86169508 -0.77310475 -0.74742818]\n",
-      " [ 0.81255861  2.26285536  1.76611306]\n",
-      " [-0.31367217 -1.55867269 -2.71347742]]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import sys, os, git\n",
-    "current_path = os.getcwd()\n",
-    "git_repo = git.Repo(current_path, search_parent_directories=True)\n",
-    "git_path = git_repo.git.rev_parse(\"--show-toplevel\")\n",
-    "sys.path.append(git_path+\"/python-codes/\")\n",
-    "\n",
-    "from InitializeSimulation import InitializeSimulation\n",
-    "\n",
-    "self = InitializeSimulation(number_atoms=[2, 3],\n",
-    "    epsilon=[0.1, 1.0], # kcal/mol\n",
-    "    sigma=[3, 6], # A\n",
-    "    atom_mass=[1, 1], # g/mol\n",
-    "    box_dimensions=[20, 20, 20], # A\n",
-    "    )\n",
-    "print(\"Atom positions:\")\n",
-    "print(self.atoms_positions)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.4"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/tests/input.lammps b/tests/input.lammps
deleted file mode 100644
index 8e82d47..0000000
--- a/tests/input.lammps
+++ /dev/null
@@ -1,55 +0,0 @@
-# LAMMPS input file 
-
-include variable.lammps
-
-# main parameters
-units real
-dimension 3
-atom_style full
-pair_style lj/cut 10 # /coul/long
-#kspace_style ewald 1e-4
-boundary p p p
-
-read_data initial.data
-include PARM.lammps
-
-neigh_modify every 5
-
-thermo ${thermo_minimize}
-dump mydmp all custom ${dumping_minimize} lammps-output/dump.md.lammpstrj id type x y z vx vy vz
-min_style sd
-minimize 1.0e-10 1.0e-10 ${minimization_steps} ${minimization_steps}
-min_style cg
-undump mydmp
-reset_timestep 0
-
-velocity all create ${temp} 4928459
-fix mynve all nve
-fix mytber all temp/berendsen ${temp} ${temp} ${tau_temp}
-if "${pber} == 1" then "fix mypber all press/berendsen iso ${press} ${press} ${tau_press} modulus 1"
-timestep ${time_step}
-
-thermo ${thermo}
-dump mydmp all custom ${dump} lammps-output/dump.md.lammpstrj id type x y z vx vy vz
-
-variable Ecoul equal ecoul
-variable Evdwl equal evdwl
-variable Epot equal pe
-variable Ekin equal ke
-variable Etot equal v_Epot+v_Ekin
-variable volume equal vol
-variable pressure equal press
-variable temperature equal temp
-variable mass equal mass(all)
-variable density equal v_mass/v_volume/6.022e23*(1e8)^3 # g/cm3
-fix myat1 all ave/time ${thermo} 1 ${thermo} v_Epot file lammps-output/Epot.dat
-fix myat2 all ave/time ${thermo} 1 ${thermo} v_Ekin file lammps-output/Ekin.dat
-fix myat3 all ave/time ${thermo} 1 ${thermo} v_Etot file lammps-output/Etot.dat
-fix myat4 all ave/time ${thermo} 1 ${thermo} v_Ecoul file lammps-output/Ecoul.dat
-fix myat5 all ave/time ${thermo} 1 ${thermo} v_Evdwl file lammps-output/Evdwl.dat
-fix myat6 all ave/time ${thermo} 1 ${thermo} v_pressure file lammps-output/pressure.dat
-fix myat7 all ave/time ${thermo} 1 ${thermo} v_temperature file lammps-output/temperature.dat
-fix myat8 all ave/time ${thermo} 1 ${thermo} v_volume file lammps-output/volume.dat
-fix myat9 all ave/time ${thermo} 1 ${thermo} v_density file lammps-output/density.dat
-
-run ${maximum_steps}
diff --git a/tests/prepare/test.ipynb b/tests/prepare/test.ipynb
deleted file mode 100644
index 0984629..0000000
--- a/tests/prepare/test.ipynb
+++ /dev/null
@@ -1,69 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Reference energy:\n",
-      "0.1\n",
-      "Reference distance:\n",
-      "3\n",
-      "array_epsilon_ij:\n",
-      "[ 1.   5.5  5.5  5.5  5.5  5.5  5.5 10.  10.  10. ]\n",
-      "array_sigma_ij:\n",
-      "[1.  1.5 1.5 1.5 1.5 1.5 1.5 2.  2.  2. ]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import sys, os, git\n",
-    "current_path = os.getcwd()\n",
-    "git_repo = git.Repo(current_path, search_parent_directories=True)\n",
-    "git_path = git_repo.git.rev_parse(\"--show-toplevel\")\n",
-    "sys.path.append(git_path+\"/python-codes/\")\n",
-    "\n",
-    "from Prepare import Prepare\n",
-    "\n",
-    "self = Prepare(number_atoms=[2, 3],\n",
-    "    epsilon=[0.1, 1.0], # kcal/mol\n",
-    "    sigma=[3, 6], # A\n",
-    "    atom_mass=[1, 1], # g/mol\n",
-    "    )\n",
-    "print(\"Reference energy:\")\n",
-    "print(self.reference_energy)\n",
-    "print(\"Reference distance:\")\n",
-    "print(self.reference_distance)\n",
-    "print(\"array_epsilon_ij:\")\n",
-    "print(self.array_epsilon_ij)\n",
-    "print(\"array_sigma_ij:\")\n",
-    "print(self.array_sigma_ij)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.4"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/tests/run.ipynb b/tests/run.ipynb
deleted file mode 100644
index 95a9be5..0000000
--- a/tests/run.ipynb
+++ /dev/null
@@ -1,248 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import sys, os, git, time\n",
-    "\n",
-    "current_path = os.getcwd()\n",
-    "git_repo = git.Repo(current_path, search_parent_directories=True)\n",
-    "git_path = git_repo.git.rev_parse(\"--show-toplevel\")\n",
-    "sys.path.append(git_path+\"/python-codes/\")\n",
-    "\n",
-    "from InitializeSimulation import InitializeSimulation\n",
-    "from Utilities import Utilities\n",
-    "from Outputs import Outputs\n",
-    "from MolecularDynamics import MolecularDynamics\n",
-    "from MonteCarlo import MonteCarlo\n",
-    "\n",
-    "import numpy as np"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "object.__init__() takes exactly one argument (the instance to initialize)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m/home/simon/Git/MDCourse/python-codes/tests/run.ipynb Cell 2\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39mself\u001b[39m \u001b[39m=\u001b[39m MonteCarlo(number_atoms\u001b[39m=\u001b[39;49m[\u001b[39m100\u001b[39;49m, \u001b[39m400\u001b[39;49m],\n\u001b[1;32m      <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m     epsilon\u001b[39m=\u001b[39;49m[\u001b[39m0.1\u001b[39;49m, \u001b[39m1.0\u001b[39;49m], \u001b[39m# kcal/mol\u001b[39;49;00m\n\u001b[1;32m      <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m     sigma\u001b[39m=\u001b[39;49m[\u001b[39m3\u001b[39;49m, \u001b[39m6\u001b[39;49m], \u001b[39m# A\u001b[39;49;00m\n\u001b[1;32m      <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m     atom_mass\u001b[39m=\u001b[39;49m[\u001b[39m1\u001b[39;49m, \u001b[39m1\u001b[39;49m], \u001b[39m# g/mol\u001b[39;49;00m\n\u001b[1;32m      <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m     \u001b[39m# atom_charge=[0], # in elementary charge units\u001b[39;49;00m\n\u001b[1;32m      <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=5'>6</a>\u001b[0m     Lx\u001b[39m=\u001b[39;49m\u001b[39m500\u001b[39;49m, \u001b[39m# A\u001b[39;49;00m\n\u001b[1;32m      <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=6'>7</a>\u001b[0m     Ly\u001b[39m=\u001b[39;49m\u001b[39m500\u001b[39;49m, \u001b[39m# A\u001b[39;49;00m\n\u001b[1;32m      <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=7'>8</a>\u001b[0m     Lz\u001b[39m=\u001b[39;49m\u001b[39m500\u001b[39;49m, \u001b[39m# A\u001b[39;49;00m\n\u001b[1;32m      <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=8'>9</a>\u001b[0m     minimization_steps\u001b[39m=\u001b[39;49m\u001b[39m0\u001b[39;49m,\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=9'>10</a>\u001b[0m     maximum_steps\u001b[39m=\u001b[39;49m\u001b[39m0\u001b[39;49m,\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=10'>11</a>\u001b[0m     desired_temperature\u001b[39m=\u001b[39;49m\u001b[39m100\u001b[39;49m,\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=11'>12</a>\u001b[0m     desired_pressure\u001b[39m=\u001b[39;49m\u001b[39m1\u001b[39;49m,\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=12'>13</a>\u001b[0m     thermo \u001b[39m=\u001b[39;49m \u001b[39m250\u001b[39;49m,\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=13'>14</a>\u001b[0m     dump \u001b[39m=\u001b[39;49m \u001b[39m250\u001b[39;49m,  \n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=14'>15</a>\u001b[0m     \u001b[39m#tau_temp = 100, # fs\u001b[39;49;00m\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=15'>16</a>\u001b[0m     \u001b[39m#tau_press= 1000, # fs\u001b[39;49;00m\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=16'>17</a>\u001b[0m     time_step\u001b[39m=\u001b[39;49m\u001b[39m1\u001b[39;49m, \u001b[39m# fs\u001b[39;49;00m\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=17'>18</a>\u001b[0m     seed\u001b[39m=\u001b[39;49m\u001b[39m219817\u001b[39;49m,\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=18'>19</a>\u001b[0m     data_folder \u001b[39m=\u001b[39;49m \u001b[39m\"\u001b[39;49m\u001b[39mmccode-output/\u001b[39;49m\u001b[39m\"\u001b[39;49m)\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=19'>20</a>\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrun()\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=20'>21</a>\u001b[0m \u001b[39m# run lammps for comparison\u001b[39;00m\n\u001b[1;32m     <a href='vscode-notebook-cell:/home/simon/Git/MDCourse/python-codes/tests/run.ipynb#W1sZmlsZQ%3D%3D?line=21'>22</a>\u001b[0m \u001b[39m#os.system(\"/home/simon/Softwares/lammps-2Aug2023/src/lmp_serial -in input.lammps > /dev/null\")\u001b[39;00m\n",
-      "File \u001b[0;32m~/Git/MDCourse/python-codes/python-codes/MonteCarlo.py:27\u001b[0m, in \u001b[0;36mMonteCarlo.__init__\u001b[0;34m(self, maximum_steps, displace_mc, mu, *args, **kwargs)\u001b[0m\n\u001b[1;32m     25\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdisplace_mc \u001b[39m=\u001b[39m displace_mc\n\u001b[1;32m     26\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mmu \u001b[39m=\u001b[39m mu\n\u001b[0;32m---> 27\u001b[0m \u001b[39msuper\u001b[39;49m()\u001b[39m.\u001b[39;49m\u001b[39m__init__\u001b[39;49m(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m     29\u001b[0m \u001b[39m#self.cut_off /= self.reference_distance\u001b[39;00m\n\u001b[1;32m     30\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdisplace_mc \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
-      "File \u001b[0;32m~/Git/MDCourse/python-codes/python-codes/InitializeSimulation.py:24\u001b[0m, in \u001b[0;36mInitializeSimulation.__init__\u001b[0;34m(self, number_atoms, Lx, Ly, Lz, epsilon, sigma, atom_mass, seed, desired_temperature, desired_pressure, *args, **kwargs)\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m__init__\u001b[39m(\u001b[39mself\u001b[39m,\n\u001b[1;32m     11\u001b[0m              number_atoms,\n\u001b[1;32m     12\u001b[0m              Lx,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     22\u001b[0m              \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs,\n\u001b[1;32m     23\u001b[0m              ):\n\u001b[0;32m---> 24\u001b[0m     \u001b[39msuper\u001b[39;49m()\u001b[39m.\u001b[39;49m\u001b[39m__init__\u001b[39;49m(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m     26\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mnumber_atoms \u001b[39m=\u001b[39m number_atoms\n\u001b[1;32m     27\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mLx \u001b[39m=\u001b[39m Lx\n",
-      "File \u001b[0;32m~/Git/MDCourse/python-codes/python-codes/Utilities.py:16\u001b[0m, in \u001b[0;36mUtilities.__init__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m__init__\u001b[39m(\u001b[39mself\u001b[39m,\n\u001b[1;32m     14\u001b[0m              \u001b[39m*\u001b[39margs,\n\u001b[1;32m     15\u001b[0m              \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs):\n\u001b[0;32m---> 16\u001b[0m     \u001b[39msuper\u001b[39;49m()\u001b[39m.\u001b[39;49m\u001b[39m__init__\u001b[39;49m(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
-      "File \u001b[0;32m~/Git/MDCourse/python-codes/python-codes/Outputs.py:23\u001b[0m, in \u001b[0;36mOutputs.__init__\u001b[0;34m(self, thermo, dump, thermo_minimize, dumping_minimize, data_folder, *args, **kwargs)\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdump \u001b[39m=\u001b[39m dump\n\u001b[1;32m     22\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdata_folder \u001b[39m=\u001b[39m data_folder\n\u001b[0;32m---> 23\u001b[0m \u001b[39msuper\u001b[39;49m()\u001b[39m.\u001b[39;49m\u001b[39m__init__\u001b[39;49m(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m     25\u001b[0m \u001b[39mif\u001b[39;00m os\u001b[39m.\u001b[39mpath\u001b[39m.\u001b[39mexists(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdata_folder) \u001b[39mis\u001b[39;00m \u001b[39mFalse\u001b[39;00m:\n\u001b[1;32m     26\u001b[0m     os\u001b[39m.\u001b[39mmkdir(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdata_folder)\n",
-      "\u001b[0;31mTypeError\u001b[0m: object.__init__() takes exactly one argument (the instance to initialize)"
-     ]
-    }
-   ],
-   "source": [
-    "self = MonteCarlo(number_atoms=[100, 400],\n",
-    "    epsilon=[0.1, 1.0], # kcal/mol\n",
-    "    sigma=[3, 6], # A\n",
-    "    atom_mass=[1, 1], # g/mol\n",
-    "    # atom_charge=[0], # in elementary charge units\n",
-    "    Lx=500, # A\n",
-    "    Ly=500, # A\n",
-    "    Lz=500, # A\n",
-    "    minimization_steps=0,\n",
-    "    maximum_steps=0,\n",
-    "    desired_temperature=100,\n",
-    "    desired_pressure=1,\n",
-    "    thermo = 250,\n",
-    "    dump = 250,  \n",
-    "    #tau_temp = 100, # fs\n",
-    "    #tau_press= 1000, # fs\n",
-    "    time_step=1, # fs\n",
-    "    seed=219817,\n",
-    "    data_folder = \"mccode-output/\")\n",
-    "self.run()\n",
-    "# run lammps for comparison\n",
-    "#os.system(\"/home/simon/Softwares/lammps-2Aug2023/src/lmp_serial -in input.lammps > /dev/null\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Case 1"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "-6.30730313864524e-22 0.114\n"
-     ]
-    }
-   ],
-   "source": [
-    "ti = time.time()\n",
-    "\n",
-    "def calculate_r(self, position_i, positions_j):\n",
-    "    \"\"\"Calculate the shortest distance between position_i and positions_j.\n",
-    "    # to fix : use the MDAnalysis option\n",
-    "    \"\"\"\n",
-    "    rij = (np.remainder(position_i - positions_j\n",
-    "                        + self.box_size/2., self.box_size) - self.box_size/2.)\n",
-    "    return np.linalg.norm(rij, axis=1)\n",
-    "\n",
-    "energy_potential = 0\n",
-    "for position_i, sigma_i, epsilon_i in zip(self.atoms_positions,\n",
-    "                                            self.atoms_sigma,\n",
-    "                                            self.atoms_epsilon):\n",
-    "    r = self.calculate_r(position_i, self.atoms_positions)\n",
-    "    sigma_j = self.atoms_sigma\n",
-    "    epsilon_j = self.atoms_epsilon\n",
-    "    sigma_ij = np.array((sigma_i+sigma_j)/2)\n",
-    "    epsilon_ij = np.array((epsilon_i+epsilon_j)/2)\n",
-    "    energy_potential_i = np.sum(4*epsilon_ij[r>0]*(np.power(sigma_ij[r>0]/r[r>0], 12)-np.power(sigma_ij[r>0]/r[r>0], 6)))\n",
-    "    energy_potential += energy_potential_i\n",
-    "\n",
-    "tf = time.time()\n",
-    "print(energy_potential/2, np.round(tf-ti,3))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Case 2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "import MDAnalysis as mda\n",
-    "from MDAnalysis import analysis\n",
-    "from MDAnalysis.analysis import distances"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "-6.307298880441376e-22 0.018\n"
-     ]
-    }
-   ],
-   "source": [
-    "epsilon_ij = []\n",
-    "for i in range(self.total_number_atoms):\n",
-    "    for j in range(i + 1, self.total_number_atoms):\n",
-    "        epsilon_i = self.atoms_epsilon[i]\n",
-    "        epsilon_j = self.atoms_epsilon[j]\n",
-    "        epsilon_ij.append((epsilon_i+epsilon_j)/2)\n",
-    "epsilon_ij = np.array(epsilon_ij)\n",
-    "sigma_ij = []\n",
-    "for i in range(self.total_number_atoms):\n",
-    "    for j in range(i + 1, self.total_number_atoms):\n",
-    "        sigma_i = self.atoms_sigma[i]\n",
-    "        sigma_j = self.atoms_sigma[j]\n",
-    "        sigma_ij.append((sigma_i+sigma_j)/2)\n",
-    "sigma_ij = np.array(sigma_ij)\n",
-    "\n",
-    "box = np.array([self.box_size[0], self.box_size[1], self.box_size[2], 90, 90, 90])\n",
-    "\n",
-    "ti = time.time()\n",
-    "\n",
-    "r_ij = mda.analysis.distances.self_distance_array(self.atoms_positions, box)\n",
-    "\n",
-    "energy_potential = np.sum(4*epsilon_ij*(np.power(sigma_ij/r_ij, 12)-np.power(sigma_ij/r_ij, 6)))\n",
-    "\n",
-    "tf = time.time()\n",
-    "print(energy_potential, np.round(tf-ti,3))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[166.66666666666666, 166.66666666666666, 166.66666666666666, 90, 90, 90]"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[166.66666667, 166.66666667, 166.66666667],\n",
-       "       [ 90.        ,  90.        ,  90.        ]])"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.vstack([box_size, box_geometry])"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.4"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/tests/run.py b/tests/run.py
deleted file mode 100644
index 6250df2..0000000
--- a/tests/run.py
+++ /dev/null
@@ -1,60 +0,0 @@
-#!/usr/bin/env python
-# coding: utf-8
-
-# In[ ]:
-
-
-from InitializeSimulation import InitializeSimulation
-from Utilities import Utilities
-from Outputs import Outputs
-from MolecularDynamics import MolecularDynamics
-from MonteCarlo import MonteCarlo
-
-
-# In[ ]:
-
-
-import numpy as np
-
-
-# In[ ]:
-
-
-self = MolecularDynamics(number_atoms=[300, 100],
-                      epsilon=[1, 1],
-                      sigma=[1, 5],
-                      atom_mass= [1, 1],
-                      Lx=30,
-                      Ly=30,
-                      Lz=30,
-                      minimization_steps = 20,
-                      maximum_steps=2000,
-                      desired_temperature=300,
-                      thermo = 100,
-                      dump = 100,  
-                      tau_temp = 100,
-                      tau_press= 1000,
-                      time_step=1,
-                      seed=219817,
-                      )
-self.run()
-
-
-# In[ ]:
-
-
-x = MonteCarlo(number_atoms=[10, 2],
-               epsilon=[1, 0.1],
-               sigma=[1, 4],
-               atom_mass= [1, 1],
-               Lx=20,
-               Ly=20,
-               Lz=20,
-               maximum_steps=1000,
-               displace_mc = 0.5,
-               seed=6987,
-               dump = 10,
-               thermo = 10,
-               )
-x.run()
-
diff --git a/tests/variable.lammps b/tests/variable.lammps
deleted file mode 100644
index 9b87a07..0000000
--- a/tests/variable.lammps
+++ /dev/null
@@ -1,14 +0,0 @@
-# LAMMPS variable file 
-
-variable thermo equal 250
-variable dump equal 250
-variable thermo_minimize equal 25
-variable dumping_minimize equal 10
-variable time_step equal 1.0
-variable minimization_steps equal 0
-variable maximum_steps equal 0
-variable temp equal 100.0
-variable tau_temp equal 100.0
-variable press equal 0.9999999999999999
-variable tau_press equal 999.9999999999999
-variable pber equal 1