skalierung_lp.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e466ee10",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import os\n",
    "from scipy.optimize import curve_fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5cb662cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "p = r\"D:\\Uni\\Masterarbeit\\Daten\\Approx_skalierbarkeit\"\n",
    "p_neu = r\"D:\\Uni\\Masterarbeit\\Daten\\Approx_skalierbarkeit_neu\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "281a6813",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['edges_10_scenarios_2',\n",
       " 'edges_200_scenarios_2',\n",
       " 'edges_400_scenarios_2',\n",
       " 'edges_500_scenarios_10',\n",
       " 'edges_500_scenarios_2',\n",
       " 'edges_50_scenarios_2',\n",
       " 'edges_550_scenarios_10',\n",
       " 'edges_650_scenarios_2',\n",
       " 'edges_800_scenarios_2']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(p_neu)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a3f4a141",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['edges', '10000', 'scenarios', '2']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = os.listdir(p)[0]\n",
    "a.split(\"_\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4aa0a855",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_files(p):\n",
    "    \"\"\"\n",
    "    d hat als keys die Anzahl an Szenarien und als values wieder dictionary wo als keys die Anzahl Edges mit den\n",
    "    np-arrays als Values drins stehen\n",
    "    \n",
    "    \"\"\"\n",
    "    d = {}\n",
    "    \n",
    "    for f in os.listdir(p):\n",
    "    \n",
    "        edges = int(f.split(\"_\")[1])\n",
    "        scenarios = int(f.split(\"_\")[3])\n",
    "\n",
    "        counters = np.loadtxt(os.path.join(p, f, \"counters.txt\"), dtype=int)\n",
    "        setup = np.loadtxt(os.path.join(p, f, \"setup_zeiten_s.txt\"), dtype=int)\n",
    "        loop = np.loadtxt(os.path.join(p, f, \"loop_zeiten_s.txt\"), dtype=int)\n",
    "        \n",
    "        d_f = {'counters': counters, 'setup_zeiten': setup, 'loop_zeiten': loop}\n",
    "        \n",
    "        # falls es zu dieser Anzahl an szenarien noch keinen Eintrag gibt, lege ihn an\n",
    "        if scenarios in d.keys():\n",
    "            d[scenarios][edges] = d_f\n",
    "        elif scenarios not in d.keys():\n",
    "            d[scenarios] = {edges : d_f}\n",
    "            \n",
    "    return d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "accc8107",
   "metadata": {},
   "outputs": [],
   "source": [
    "d = load_files(p)\n",
    "d_neu = load_files(p_neu)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2d4779c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# bearbeite counters\n",
    "def do_counters(d, scenarios=2):\n",
    "    \n",
    "    edges_ = sorted(d[scenarios].keys())\n",
    "    \n",
    "    means = []\n",
    "    stds = []\n",
    "    \n",
    "    for edges in edges_:\n",
    "        means.append(d[scenarios][edges]['counters'].mean())\n",
    "        stds.append(d[scenarios][edges]['counters'].std())\n",
    "    \n",
    "    return edges_, means, stds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a828fcd6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# bearbeite counters\n",
    "def do_loop_times(d, scenarios=2):\n",
    "    \n",
    "    edges_ = sorted(d[scenarios].keys())\n",
    "    \n",
    "    means = []\n",
    "    stds = []\n",
    "    \n",
    "    for edges in edges_:\n",
    "        means.append(d[scenarios][edges]['loop_zeiten'].mean())\n",
    "        stds.append(d[scenarios][edges]['loop_zeiten'].std())\n",
    "    \n",
    "    return edges_, means, stds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a2a21aab",
   "metadata": {},
   "outputs": [],
   "source": [
    "e, m_c, s_c = do_counters(d)\n",
    "e, m_loop, s_loop = do_loop_times(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "02a262c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ErrorbarContainer object of 3 artists>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,10))\n",
    "ax.scatter(e, m_c)\n",
    "ax.set_title(\"Anzahl an hinzugefügten Min-Cut Constraints\", fontsize=20)\n",
    "ax.set_xlabel(\"Anzahl an Kanten in Graphen\", fontsize=15)\n",
    "ax.set_ylabel(\"Anzahl hinzugefügter Constraints\", fontsize=15)\n",
    "ax.errorbar(e, m_c, s_c, fmt='None', capsize=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "941a3fcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ErrorbarContainer object of 3 artists>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,10))\n",
    "# ax.scatter(e, m_loop)\n",
    "ax.set_title(\"Zeit, bis gültige LP-Lösung gefunden ist\", fontsize=20)\n",
    "ax.set_xlabel(\"Anzahl an Kanten in Graphen\", fontsize=15)\n",
    "ax.set_ylabel(\"Benötigte Zeit [$s$]\", fontsize=15)\n",
    "ax.errorbar(e, m_loop, s_loop, fmt='o', capsize=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3a80863",
   "metadata": {},
   "source": [
    "## Fitten"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "f0d00cf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# linearer fit:\n",
    "def f_lin(x, m, n):\n",
    "    return m * x + n\n",
    "\n",
    "# exponentieller Fit:\n",
    "def f_exp(x, a, b):\n",
    "    return a * np.exp(b *x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "23f57224",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0.29578979, -27.44718156])"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popt_lin, pcov_lin = curve_fit(f_lin, e, m_c)\n",
    "popt_lin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "e43300ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[10, 100, 1500, 1800, 2000, 3500, 4500, 4950, 7500, 10000, 12000]"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "03a7630d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.0,\n",
       " 0.0,\n",
       " 10.70754716981132,\n",
       " 16.926829268292682,\n",
       " 23.386666666666667,\n",
       " 140.375,\n",
       " 425.875,\n",
       " 313.875,\n",
       " 1412.5438596491229,\n",
       " 3126.12,\n",
       " 18791.25]"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m_loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "1676d3ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.69420596, 0.00085037])"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popt_exp, pcov_exp = curve_fit(f_exp, e, m_loop, maxfev=50000, p0=[0,0])#, bounds=([-500, 0, -50], [500, 10, 50]))\n",
    "popt_exp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "861250af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2176ea569c8>"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,10))\n",
    "ax.scatter(e, m_c)\n",
    "ax.set_title(\"Anzahl an hinzugefügten Min-Cut Constraints\", fontsize=20)\n",
    "ax.set_xlabel(\"Anzahl an Kanten in Graphen\", fontsize=15)\n",
    "ax.set_ylabel(\"Anzahl hinzugefügter Constraints\", fontsize=15)\n",
    "ax.errorbar(e, m_c, s_c, fmt='None', capsize=4)\n",
    "\n",
    "lp = np.linspace(0, 12000, 100)\n",
    "\n",
    "ax.plot(lp, f_lin(lp, *popt_lin), c='orange', label=f\"Fit: {popt_lin[0]:.3}x + {popt_lin[1]:.4}\")\n",
    "ax.legend(fontsize=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "ee4affd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x21770c90508>"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,10))\n",
    "# ax.scatter(e, m_loop)\n",
    "ax.set_title(\"Zeit, bis gültige LP-Lösung gefunden ist\", fontsize=20)\n",
    "ax.set_xlabel(\"Anzahl an Kanten in Graphen\", fontsize=15)\n",
    "ax.set_ylabel(\"Benötigte Zeit [$s$]\", fontsize=15)\n",
    "ax.errorbar(e[:], m_loop[:], s_loop[:], fmt='o', capsize=4)\n",
    "\n",
    "lp = np.linspace(0, 12000, 100)\n",
    "\n",
    "ax.plot(lp, f_exp(lp, *popt_exp), c='orange', label=f\"Fit: ${popt_exp[0]:.3} * e^{{{popt_exp[1]:.3} * x}}$\")\n",
    "ax.legend(fontsize=20)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f7ae50b",
   "metadata": {},
   "source": [
    "## Meine opt-Zeiten sind useless, weil darin aus Versehen nochmal die Setup-Zeiten gespeichert wurden.\n",
    "\n",
    "Ich kann also nicht sagen, ob der LP-Alg der Teil ist, der exponentiell länger benötigt\n",
    "\n",
    "Wenn ich gute opt Zeiten hätte, könnte ich einmal schauen, wie die sich von Iteration zu Iteration ändern und außerdem könnte ich schauen, wie die sich unterscheiden, wenn die Problemstellung größer wird."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4e1cb8e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "56.78333333333333"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# so viele Minuten dauerten die 8 4500er Simulationen\n",
    "sum(loop_zeiten[-1]/60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "bc7f2f39",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1500 Kanten: 318 Simulationen in 56.75 Minuten (entspricht 10.71s/Simulation)\n",
      "1800 Kanten: 205 Simulationen in 57.83 Minuten (entspricht 16.93s/Simulation)\n",
      "2000 Kanten: 150 Simulationen in 58.47 Minuten (entspricht 23.39s/Simulation)\n",
      "4500 Kanten: 8 Simulationen in 56.78 Minuten (entspricht 425.88s/Simulation)\n"
     ]
    }
   ],
   "source": [
    "for i, l in enumerate(loop_zeiten):\n",
    "    print(f\"{number_edges[i]} Kanten: {len(l)} Simulationen in {sum(l/60):.2f} Minuten (entspricht {mean_loop_zeiten[i]:.2f}s/Simulation)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72cbf0ad",
   "metadata": {},
   "source": [
    "# Jetzt neu mit der aktualisierten Version des LP-Algs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f26d94c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "e2, m_c2, s_c2 = do_counters(d_neu)\n",
    "e2, m_loop2, s_loop2 = do_loop_times(d_neu)\n",
    "e10, m_c10, s_c10 = do_counters(d_neu, 10)\n",
    "e10, m_loop10, s_loop10 = do_loop_times(d_neu, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bbca112c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ErrorbarContainer object of 3 artists>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,10))\n",
    "ax.scatter(e2, m_c2)\n",
    "ax.set_title(\"Anzahl an hinzugefügten Min-Cut Constraints für 2 Szenarien\", fontsize=20)\n",
    "ax.set_xlabel(\"Anzahl an Kanten in Graphen\", fontsize=15)\n",
    "ax.set_ylabel(\"Anzahl hinzugefügter Constraints\", fontsize=15)\n",
    "ax.errorbar(e2, m_c2, s_c2, fmt='None', capsize=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "abd9f50f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ErrorbarContainer object of 3 artists>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,10))\n",
    "ax.scatter(e10, m_c10)\n",
    "ax.set_title(\"Anzahl an hinzugefügten Min-Cut Constraints für 10 Szenarien\", fontsize=20)\n",
    "ax.set_xlabel(\"Anzahl an Kanten in Graphen\", fontsize=15)\n",
    "ax.set_ylabel(\"Anzahl hinzugefügter Constraints\", fontsize=15)\n",
    "ax.errorbar(e10, m_c10, s_c10, fmt='None', capsize=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11e97036",
   "metadata": {},
   "source": [
    "### Zeit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3d490ad0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ErrorbarContainer object of 3 artists>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MTZfW2lWttSNaa3dL9/o9Mt3Jrx6W7gQmo18aWxb/kXa7jah33Ma071LLu2VVTap5Q9vKrD43Fn2v9LZb5nI2ZKHmpT5PJs1z0BLPc/ykOitqBp9nm2JT2mqj9wz33W0/nK4768taa8/e2GWtV1TX3fpv0/UyuFGSe4+t+z7pThb43SQP7bv1jlvYVm6xxLayKZf7+tN0wfXw1to9W2t/0Vp7QeuuHb7UCeOmee0Hud3DvAmvsAL6Mwv/bZKL051Z+KdLzPL1dL+U3qs/JmxTLHR3nPWvq7vU5Msp3K+/P325C2qtXdlaO6219tIkj+sH77+MWRfW8bvjI/qzMt5uwjw/7O8njdtzwrANuTrTva4L9e416fIJmfA8knyuv5/qTLVbqDPTnQjq7v3xc+Pu399/YcK4tNYubq0d21p7TLouxr+a5C4jk/wwE9q9qlbl2i7dG6219uN0ZyTeaZH3xqT23ZDT0/1fnnR5mUnLmuXnRrKB90rfRXq3Gazj67m2zSf11rjfhGGDfk8s4/NsJT6TN0dbjS/3FunOBn2fJP+wsXtcl+EnC6scWfeu6X6k+kWSB7fWFuutsTm2lV/r798zYdx9Z7ieQW/3MC/CK8xYf5zNm9Od8fARrbXvLDVP303w1en2NP1LVa2esNwdqurOyyhh4TIEuyxS38L15E5axrJGrUry0rrudSPvkOQv03WXeuuGZq7uuoKT9rYsDLtswrhx/9mv65n9yZAWll3pTgAy6cvhqelC5+P7Y5AX5rllupMfTeMHmRyCJ2rdSXtOSvdl56mj46pqv6x/vGvSdTH/VpKnV9WDJi23qvYafS5bqtadlOht6bq9vXh0XFX9arpt64r0J4Wp7lqne9fYwZ19cLtl/3B0Ozo53Y8u49dDfEG6y4/Mwr+n+1/6T6N19dvnszZiWUny9zVybck+NPzt+MQz/txIa+0n6cLlvUfn6cP+K9KdtGuTtNauSNfmN8/YCZuqas9MOLlU607k9D9JHlFVfzxpuVV116q6zabWt1xTfp5t8DN5Y2yOthrV/7j0sXTHp76otfaCTVjWIVW12KWffjfdj1ZXprvsUqrq1umO779Fkke11r68gcW/Jt1nxiurar0AX1U37Pfgbopz+vv7jS17j3SXIJqJIW73MASOeYUZ6rtUvS/dGQBPSbJPVW3oWJVz2rVn6Py7dNdnfVq6syF+PN1p9W+T7pi2e6c7bvarS5RxYrrjfd5QVe9Od8Kdta211/TjF8Lncq/Jt+CL6U6ocVpVfTTdF4nHpuue9pw24eyLYx6fLpD9d7qz7/4w3Z6yh6b7Nf1VSxXQWvtWVb0w3YlS/reqjsm113m9ZZL/TfJ/xub5XlW9Ld3ZkM+oqg+mO1bxQekuSbLUiaZGnZjkgKr6r3THXF2Z5JOttU9uYJ6npzuRy+v6MLpwnddHpttWHp5ruwAunOTmEelOAPPBqvpMuksiXJYuOP92P/8OWV7gT5JU1dEbGP0Xbey6wzNy6w2s97LW2l+k62p5nyTP6H/4+USuvc7rzZM8o117orDV6b5An1NVn093nO2N07X/ryd5f2vtayPr+Od0J4R5X7+tXJpur+Yd0v2ocL8ZPMeXpdvLdkCS3UfeG49Jt33tn5H2XcK/98vZL8mXq+r96c6c+sh0P8LsPmFZs/rcWPDydJfY+XR1J8RauGbstuneX8s5E+xSnpfuTLHP6gPrwnVeH5supDxswjyPT7d3/U1V9Zfprq+5NsnO6d7zd0l3gpuLZ1DfckzzefbZdO/VZ/U/mi0cx/nqtmknGtscbbXg2HQ9Vb6V5AaLnEDouNbaGctY1h8meVlVfT3d3sXvpTvh0W+kOzt7pTt+/YJ++hen+wHwC+nC+r3XX2Re1Vpb21r7eh/0jkp3UrePJPlGutdkl3SfNZekO3HYxvr3dP9jX1VV9093wrRd011b9dh02/GsDG27h/lrA7hej5vb9eWW614ncjm3k8bmr3Qh68Rce/3U89N9uXterntt04V1HT2hjr9K8rV0X6JaRq63mWsv6v6nUzyvlu7L/o7p9rBenO6L0heSPH7C9PfL+tdFvGeSf033perSdGdB/Wa6vdR3mfJ1fkK6LpY/T/dF5K19bV9OF9THp79Rui965+XaawAemu4HvEntcFgmX+f1Nun2/l6UrivgNc9xifa4U7ovNWuT/Czdl9kHJ/nrfp79J8xzmyQv6Z/TZel+hDgrybvTXV5mmynabqnbdv2052Ts2qcr+D5YOzL9dkle2j+/X/Sv0wlJfn9sudsmeU66Y+7OHWn/z6ULbzecUMvD0gW/n6fbA/aOdHtdjx5/rhtqw378SZl8zc3t0l3W54K+/q+nu0zNPfrlvWqK1+7G6b6sn90v65wk/5Du7KUtXUAYn2fZnxsbeh4j4/8kyVf69V+Y7jJPt5o0Xxa5PuXI+HMy4Xq/6Y5tPapvv3XpfqA5cEPLS/djxvPS/XD0036+s9OdPOgpSW46Mu2B2cC1VTPhfb+B12O9mjLl51m6HyQ+29e98B5Y8n22OdtqiTrOydLv6Ymv9YRl7ZGu98PH+/Zbl+79+a10e+V/d2z6o5ex7jVj89y1n+87/WtzabrP0tcnecByX+PFtqMkd053tuWL032mn5buWNg1mfAZkiWuv76htsmctns3t6HeqrUWYOtRVcem+1J9xzZyLcktXX+c10XpLnOy11LTD0G/R/jxSe7UWjtz3vUwW1X1Z+murfi0tonX1ex7cHw0yUtaazPrmggAWxLHvMJWpD8m7z5J/nlLDa5Vtf34yWn6s7P+v3R7rd47l8IWUVU3qKr1zqBaVXun6172VcF1y1ZVO04Ydrt0x6lemeQDm7isW6XbC58MbPsGgM3JMa+wFWldV4vtl5xw2B6Z5MVV9bF0l0y4ZZLfS3d2zTPSncBmSG6Y7tqPn0jXnfTKdMd27ZOue+fT51gbs/Ge/geV09J1eV6T7vi3myQ5tLV2/hTLekVV3S3JZ9J1qd05yR+k285f31o7eYZ1A8AWRXgFtjSfT3cs3+/l2ou4n53uuMCXttbWzauwRVyR5N/SnYjknukCzfeTvCtdF9DT51gbs/Ef6Y45fWS6kzX9NN12+prW2rFTLuvYdGesfWi6Y2l/nu6YxqOSvHFG9QLAFskxrwAAAAyeY14BAAAYvC2u2/Ctb33rtmbNmnmXAQAAwIyddtpp32+tTTxHyxYXXtesWZNTTz113mUAAAAwY1X1ncXG6TYMAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADN428y6gqs5J8pMkVyW5srW253wrAgAAYGjmHl5792+tfX/eRQAAADBMug0DAAAweEMIry3JR6vqtKp6yryLAQAAYHiG0G343q21C6rqNklOqKqvt9Y+OTpBH2qfkiS77LLLPGoEAABgjua+57W1dkF/f3GS9ya5x4Rpjmyt7dla23P77bff3CUCAAAwZ3MNr1V106q6+cLfSX4/yZfnWRMAAADDM+9uw7dN8t6qWqjlP1trH5lvSQAAAAzNXMNra+3bSe42zxoAAAAYvrkf8woAAABLEV4BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABi8eV/nFQAAgBXyyhO+kSNOPGvR8QftvWsO3me3zVjRxqvW2rxrmMqee+7ZTj311HmXAQAAsEV57Os/myQ55ql7zbmSxVXVaa21PSeN020YAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDB22beBQAAwNbolSd8I0eceNai4w/ae9ccvM9um7EiGDbhFQAA5uDgfXa7Jpw+9vWfTZIc89S95lkSDJpuwwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAzeIMJrVa2qqtOr6gPzrgUAAIDhGUR4TXJQkq/NuwgAAACGae7htap2TvLgJG+cdy0AAAAM09zDa5JXJXlOkqvnXAcAAAADNdfwWlUPSXJxa+20JaZ7SlWdWlWnXnLJJZupOgAAAIZi3nte753kYVV1TpJ3JHlAVb11fKLW2pGttT1ba3tuv/32m7tGAAAA5myu4bW1dmhrbefW2pokByT5eGvtj+ZZEwAAAMMz7z2vAAAAsKRt5l3AgtbaSUlOmnMZAAAADJA9rwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4M01vFbVjavq5Kr636r6SlUdPs96AAAAGKZt5rz+XyR5QGvtp1W1bZJPVdWHW2ufm3NdAAAADMhcw2trrSX5af9w2/7W5lcRAAAAQzT3Y16ralVVnZHk4iQntNY+P+eSAAAAGJgl97xW1Ts3ctnPaa2ds9RErbWrkty9qrZL8t6quktr7ctjNTwlyVOSZJdddtnIcgAAANhSLWfP66OS/GqS7Zd5u02SRya55TSFtNbWJjkpyX4Txh3ZWtuztbbn9ttvP81iAQAAuB5Y7jGvf95aO3k5E1bVNkkuX+a02ye5orW2tqpWJ3lgkpcusyYAAAC2EssJr4cnOW+KZV7Vz3PBMqbdIclbqmpVur3A72ytfWCKdQEAALAVWDK8ttamuvZqfwbhZc3TWvtikj2mWT4AAABbn6nONlxVe1fVfVeqGAAAAJhk2kvlvCTJvgsPqurOVfWZqvp8VT1htqUBAABAZ9rwuluST408fkWS2yY5LckbquohsyoMAAAAFiz3bMMLrk5yWZJU1W3TnR14v9bax6rqwiSHJnHCJQAAAGZq2j2vX07yu/3fByRZm+TE/vEnk/zGbMoCAACAa0275/Ufkry3qu6W7tjXo/uzCyfJrdLtmQUAAICZmmrPa2vtI0n+IMkPk7w5yfNHRt8/yTdmVxoAAAB0pt3zmtbaSUlOWmRZx2xiPQAAALCeaY95XVRr7WmttVfOankAAADMxnGnn5/Tz12bz599ae79ko/nuNPPn3dJU1syvFbVX1bVbaZZaD/PrTe+LAAAAGbhuNPPz6HHfimXX9Wdouj8tety6LFf2uIC7HL2vL4yye2Xu8CqWtXPs8vGFgUAAMBsvPz4M7PuiquuM2zdFVfl5cefOaeKNs5yjnmtJP9UVZcuc5m1CfUAAAAwQxesXTfV8KFaTnj9ZJJVSbafYrmfTPKTjaoIAACAmdlxu9U5f0JQ3XG71XOoZuMtGV5ba/fbDHUAAACwAg7Zd/cceuyXrtN1ePW2q3LIvrvPsarpTX2pHAAAALYc+++xU5LkOe/+Yi6/6urstN3qHLLv7tcM31IIrwAAANdz+++xU95+8rlJkmOeutecq9k4M7vOKwAAAKwU4RUAAIDBmyq8VtULq2rHRcbtUFUvnE1ZAAAAcK1p97y+KMnOi4zbsR8PAAAs03Gnn5/Tz12bz599ae79ko/nuNPPn3dJMEjThtdK0hYZt3OSH25aOQAAsPU47vTzc+ixX8rlV12dJDl/7boceuyXBFiYYMmzDVfVk5I8qX/YkvxrVf14bLIbJ7lrko/OtjwAALj+evnxZ17n2ptJsu6Kq/Ly48/c4i5jAittOZfKuSzJD/q/K8mPklw6Ns3lST6c5HWzKw0AAK7fLli7bqrhsDVbMry21t6V5F1JUlVvTvJ3rbVvr3RhAABwfbfjdqtz/oSguuN2q+dQDQzbVMe8ttaeLLgCAMBsHLLv7lm97arrDFu97aocsu/uc6oIhms5x7yenOTA1tpX+783qLV2j5lUBgAA13MLx7U+591fzOVXXZ2dtludQ/bd3fGuMMFyjnn9SpKFvgxfzeJnGwYAAKa0/x475e0nn5skOeape825Ghiu5Rzz+uSRvw9c0WoAAABggmmv8woAAACb3XK6Da+nqu6c5LeS3C7JUa21C6vq15Jc1Fr7ySwLBAAAgKnCa1XdLMlRSR6Z5Mp+/o8kuTDJPyY5N8lfz7hGAAAAtnLTdht+RZLfSfLAJDdPUiPjPpRkvxnVBQAAANeYttvwI5Ic1Fr7RFWtGhv3nSS3n01ZAAAAcK1p97yuTvKDRcbdPMlVm1YOAAAArG/a8HpKkicuMu5RST6zaeUAAADA+qbtNvyCJB+rqo8leVeSluRBVXVwuvD6ezOuDwAAAKbb89pa+1SSvZPcKMlr0p2w6fAkd0zywNbaKTOvEAAAgK3e1Nd5ba19Osl9qmp1kl9Osra1dtnMKwMAAIDeknteq+qJVXWH8eGttXWttQsWgmtV7VRVL1yJIgEAANi6Lafb8NFJzqiqJywx3c5JXrTJFQEAAMCY5R7z+u0kR1fV26rql1ayIAAAABi33PD61CR/nuTh6fbC7rVyJQEAAMB1Lftsw621I5P8VpIfJvnvqnphVU17nVgAAACY2rSXyjkzyT2TvDLJC9OF2F1WojAAAABYMPWe09bala21v0myT5I1Sf63qg6YdWEAAACwYOrrvC5orX2iqu6a5A1J3pbkczOrCgAAAEZs0jGrrbW1rbVHJ3lKkrvOpiQAAAC4ruXseb1/kq9uaILW2puq6hNJ7jOTqgAAAGDEkuG1tfbfy1lQa+3b6a4HCwAAADPlUjcAAAAMnvAKAADA4AmvAAAADJ7wCgAAwOBt1HVeq+rOSX4rye2SHNVau7Cqfi3JRa21n8yyQAAAAJgqvFbVzZIcleSRSa7s5/9IkguT/GOSc5P89YxrBAAAYCs3bbfhVyT5nSQPTHLzJDUy7kNJ9ptRXQAAAHCNabsNPyLJQa21T1TVqrFx30ly+9mUBQAAANeads/r6iQ/WGTczZNctWnlAAAAwPqmDa+nJHniIuMeleQzm1YOAAAArG/absMvSPKxqvpYknclaUkeVFUHpwuvvzfj+gAAAGC6Pa+ttU8l2TvJjZK8Jt0Jmw5PcsckD2ytnTLzCgEAANjqTX2d19bap5Pcp6pWJ/nlJGtba5fNvDIAAADoTbXntapeWFU7JklrbV1r7YKF4FpVO1TVC1eiSAAAALZu056w6UVJdl5k3I79eAAAAJipacNrpTtJ0yQ7J/nhppUDAAAA61vymNeqelKSJ/UPW5J/raofj0124yR3TfLR2ZYHAAAAyzth02VJftD/XUl+lOTSsWkuT/LhJK+bXWkAAADQWTK8ttbele6arqmqNyd5cWvt7JUuDAAAABZMe6mcNye5XVXdbsK4q5P8OMmZrbVfbHJlAAAA0Js2vJ6U656wadIJnH5eVW9M8lettas2oTYAAABIMn14fWCSNyX5UJL3J7kkyfZJHp7kQUmeneTXkzwvyU+TPH9mlQIAALDVmja8PiPJW1prh40NP76qDktyYGvtoVW1TZIDI7wCAAAwA9Ne5/X3k3xqkXGfTnL//u9PJtlhY4sCAACAUdOG10uTPGyRcQ/LtZfQuUm6S+oAAADAJpu22/DLkvxLVa1J8l9Z/5jXZ/bT3T/JKTOqEQAAgK3cVOG1tfaaqjo/yaFJXtvPf2WSM5I8orV2XD/pPyW5fHZlAgAAsDWbds9rWmvvTfLeqrpBur2ul7TWrh6b5vszqg8AAACmD68L+sB60QxrAQAAgImWDK9VdXK6S+B8tapOSdI2NH1r7R6zKg4AAACS5e15/UqSdSN/bzC8AgAAwKwtGV5ba08e+fvAFa0GAAAAJpjqOq9V9cKq2nGRcTtU1QtnUxYAAABca6rwmuRFSXZeZNyO/XgAAACYqWnDa2XxY153TvLDTSsHAAAA1recsw0/KcmT+octyb9W1Y/HJrtxkrsm+ehsywMAAIDlnW34siQ/6P+uJD9KcunYNJcn+XCS182uNAAAAOgs52zD70ryriSpqjcn+bvW2rdXujAAAABYsJw9r9dYuGxOf8bhvZLcMt1e2c+11i6YfXkAAAAwZXitqhskeU2SP0uyamTUVVV1ZJJnttaunmF9AAAAsPTZhqvq5Kq6c//wxUn+OMnzkqxJsrq/f14//LBpVl5Vt6uqT1TV16rqK1V10DTzAwAAsHVYzp7XryRZ1//9xCQvaK3988j4c5O8vKpakr9M8sIp1n9lkme31r5QVTdPclpVndBa++oUywAAAOB6bjknbHryyMPbJPniIpN+sR+/bK217yX5Xv/3T6rqa0l2SiK8AgAAcI3ldBu+uKr26B9+I8kBi0x6QJIzN7aQqlqTZI8kn9/YZQAAAHD9tJxuw69NclH/998neUdV7ZLk3f3w2yR5dJL7Z/Fgu0FVdbMk70nyrNbajyeMf0qSpyTJLrvssjGrAAAAYAu2nG7Dh4/8/c6qWpvk8CRHJNk2yRVJTkuyX2vthGkLqKpt0wXXt7XWjl2khiOTHJkke+65Z5t2HQAAAGzZprpUTpK01j6a5KP9ZXNuneT7G3t5nKqqJG9K8rXW2is2ZhkAAABc/y15zOtiWmtXt9Yu3sTrut47yROSPKCqzuhvD9qE5QEAAHA9NPWe1ySpqt2S7JzkxuPjWmsfWu5yWmufSlIbUwMAAABbj6nCa1XdOckxSe6cyaGzJVk1g7oAAADgGtPueX19khsmeUS6a7FePvOKAAAAYMy04XWPJAe01j6wEsUAAADAJNOesOlbmXCcKwAAAKykacPrs5M8r6ruuBLFAAAAwCTTdhv+pyQ7Jfl6VZ2TZO34BK21e2x6WQAAAHCtacPrl/sbAAAAbDZThdfW2pNXqhAAAABYzLR7XpNcc73X30pyuyRHtdYurKpfS3JRa+0nsywQAAAApgqvVXWzJEcleVSSK/r5P5LkwiT/mOTcJH894xoBAADYyk17tuFXJPmdJHsnuXmSGhn3oST7zaguAAAAuMa03YYfkeSg1tonqmrV2LjvJLn9bMoCAACAa02753V1kh8sMu7mSa7atHIAAABgfdOG11OSPHGRcY9K8plNKwcAAADWN2234Rck+VhVfSzJu5K0JA+qqoPThdffm3F9AAAAMN2e19bap9KdrOlGSV6T7oRNhye5Y5IHttZOmXmFAAAAbPWmvs5ra+3TSe5TVauT/HKSta21y2ZeGQAAAPSmPeb1Gq21dUkuS/LrVXWb2ZUEAAAA17Ws8FpVB1TVO6rqPVX1h/2wFyb5XpKTk3yvH3fTFawVAACArdSS4bWq/izJfya5Q5JbJHlzVb0yycFJnp/kwUmem+5Y2OevXKkAAABsrZZzzOszk7yqtfZXSVJVf5TkLUkOaq29pp/mI1V1ZZKnJXneilQKAADAVms53YZ/Ncl/jTx+X7qzDJ82Nt2pSW4/o7oAAADgGssJr6uT/Gzk8cKZhX8xNt3lSbadRVEAAAAwarlnG27LHAYAAAAzt9zrvB7fH9M66sSxYVNfMxYAAACWYzmB8/AVrwIAAAA2YMnw2loTXgEAAJir5R7zCgAAAHMjvAIAADB4wisAAACDJ7wCAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB428y7AACAoXnlCd/IESeetej4g/beNQfvs9tmrAgA4RUAYMzB++x2TTh97Os/myQ55ql7zbMkgK2ebsMAAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAye8AoAAMDgCa8AAAAMnvAKAADA4AmvAAAADN5cw2tVHVVVF1fVl+dZBwAAAMM27z2vRyfZb841AAAAMHBzDa+ttU8muXSeNQAAADB8897zCgAAAEvaIsJrVT2lqk6tqlMvueSSeZcDAADAZrZFhNfW2pGttT1ba3tuv/328y4HAACAzWyLCK8AAABs3eZ9qZy3J/lskt2r6ryq+pN51gMAAMAwbTPPlbfWHjfP9QMAALBl0G0YAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwdtm3gUAAMDW6JUnfCNHnHjWdYatee4Hr/n7oL13zcH77La5y4LBEl4BAGAODt5nN+EUpqDbMAAAAINnzysAAMD11PWpe7rwCgAAcD11feqertswAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweMIrAMAijjv9/Jx+7tp8/uxLc++XfDzHnX7+vEsC2GoJrwAAExx3+vk59Ngv5fKrrk6SnL92XQ499ksCLMCcCK8AABO8/Pgzs+6Kq64zbN0VV+Xlx585p4oAtm7CKwDABBesXTfVcABWlvAKADDBjtutnmo4ACtLeAUAmOCQfXfP6m1XXWfY6m1X5ZB9d59TRQBbt23mXQAAwBDtv8dOSZLnvPuLufyqq7PTdqtzyL67XzMcgM1LeAUAWMT+e+yUt598bpLkmKfuNedqALZuug0DAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweMIrAAAAgye8AgAAMHjCKwAAAIMnvAIAADB4wisAAACDJ7wCAAAweNvMuwAA2Fq98oRv5IgTz1p0/EF775qD99ltM1YEAMMlvALAnBy8z27XhNPHvv6zSZJjnrrXPEsCgMHSbRgAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQDm7LjTz8/p567N58++NPd+ycdz3Onnz7skABgc4RUA5ui408/Pocd+KZdfdXWS5Py163LosV8SYAFgjPAKAHP08uPPzLorrrrOsHVXXJWXH3/mnCoCgGESXgFgji5Yu26q4QCwtRJeAWCOdtxu9VTDAWBrJbwCwBwdsu/uWb3tqusMW73tqhyy7+5zqggAhmmbeRcAAFuz/ffYKUnynHd/MZdfdXV22m51Dtl392uGAwCduYfXqtovyRFJViV5Y2vtJXMuCQA2q/332ClvP/ncJMkxT91rztUAwDDNNbxW1aokr02yT5LzkpxSVe9vrX11nnVtjONOPz8vP/7MXLB2XXYc6K/mW0KNbPlsZwAArIR573m9R5Jvtta+nSRV9Y4kD0+yRYXXhWv0LVzqYOEafUkG86V9S6iRLZ/tDACAlTLvEzbtlOS7I4/P64dtUbaEa/RtCTWy5bOdAQCwUuYdXmvCsLbeRFVPqapTq+rUSy65ZDOUtXyPff1nc/4i1+I7f+26PPb1n93MFa1vS6iRLZ/tDACAlTTv8HpektuNPN45yQXjE7XWjmyt7dla23P77bffbMUtxzFP3Ss7LXItvp22Wz2IE29sCTWy5bOdAQCwkuYdXk9JsmtV3aGqbpjkgCTvn3NNU9sSrtG3JdTIls92BgDASpnrCZtaa1dW1TOSHJ/uUjlHtda+Ms+aNsbCiWiGfIbVLaFGtny2MwAAVsq8zzac1tqHknxo3nVsqv332GnwX9C3hBrZ8tnOAABYCfPuNgwAAABLmvueVwCAoXnlCd/IESeedZ1ha577wWv+PmjvXXPwPrtt7rIAtmrCKwDAmIP32U04BRgY3YYBAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABi8beZdAABsrV55wjdyxIlnXWfYmud+8Jq/D9p71xy8z26buywAGKRqrc27hqnsueee7dRTT513GQAAAMxYVZ3WWttz0jjdhgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGDzhFQAAgMETXgEAABg84RUAAIDBE14BAAAYPOEVAACAwRNeAQAAGLxqrc27hqlU1SVJvjOHVd86yffnsF6Wpm2GSbsMl7YZLm0zXNpmmLTLcGmb4Rp629y+tbb9pBFbXHidl6o6tbW257zrYH3aZpi0y3Bpm+HSNsOlbYZJuwyXthmuLbltdBsGAABg8IRXAAAABk94Xb4j510Ai9I2w6RdhkvbDJe2GS5tM0zaZbi0zXBtsW3jmFcAAAAGz55XAAAABk94XUJV7VdVZ1bVN6vqufOuZ2tTVUdV1cVV9eWRYbesqhOq6qz+/pdHxh3at9WZVbXvfKreOlTV7arqE1X1tar6SlUd1A/XPnNUVTeuqpOr6n/7djm8H65dBqKqVlXV6VX1gf6xthmAqjqnqr5UVWdU1an9MG0zAFW1XVW9u6q+3v/P2UvbzFdV7d6/VxZuP66qZ2mXYaiqg/vvAF+uqrf33w2uF20jvG5AVa1K8tokf5DkzkkeV1V3nm9VW52jk+w3Nuy5SU5sre2a5MT+cfq2OSDJb/TzvK5vQ1bGlUme3Vr79ST3SvL0vg20z3z9IskDWmt3S3L3JPtV1b2iXYbkoCRfG3msbYbj/q21u49cQkLbDMMRST7SWrtTkrule/9omzlqrZ3Zv1funuS3klyW5L3RLnNXVTsl+cske7bW7pJkVbrX/nrRNsLrht0jyTdba99urV2e5B1JHj7nmrYqrbVPJrl0bPDDk7yl//stSfYfGf6O1tovWmtnJ/lmujZkBbTWvtda+0L/90/SfZnYKdpnrlrnp/3Dbftbi3YZhKraOcmDk7xxZLC2GS5tM2dV9UtJfi/Jm5KktXZ5a21ttM2Q7J3kW62170S7DMU2SVZX1TZJbpLkglxP2kZ43bCdknx35PF5/TDm67atte8lXYBKcpt+uPaak6pak2SPJJ+P9pm7vlvqGUkuTnJCa027DMerkjwnydUjw7TNMLQkH62q06rqKf0wbTN/d0xySZI3993t31hVN422GZIDkry9/1u7zFlr7fwk/5zk3CTfS/Kj1tpHcz1pG+F1w2rCMKdnHi7tNQdVdbMk70nyrNbajzc06YRh2mcFtNau6rty7ZzkHlV1lw1Mrl02k6p6SJKLW2unLXeWCcO0zcq5d2vtN9MdKvT0qvq9DUyrbTafbZL8ZpJ/ba3tkeRn6bs7LkLbbEZVdcMkD0vyrqUmnTBMu6yA/ljWhye5Q5Idk9y0qv5oQ7NMGDbYthFeN+y8JLcbebxzut3uzNdFVbVDkvT3F/fDtddmVlXbpguub2utHdsP1j4D0XetOyndMSzaZf7uneRhVXVOusNQHlBVb422GYTW2gX9/cXpjt27R7TNEJyX5Ly+B0mSvDtdmNU2w/AHSb7QWruof6xd5u+BSc5urV3SWrsiybFJfifXk7YRXjfslCS7VtUd+l+WDkjy/jnXRNcGT+r/flKS940MP6CqblRVd0iya5KT51DfVqGqKt0xSF9rrb1iZJT2maOq2r6qtuv/Xp3un9jXo13mrrV2aGtt59bamnT/Tz7eWvujaJu5q6qbVtXNF/5O8vtJvhxtM3ettQuTfLeqdu8H7Z3kq9E2Q/G4XNtlONEuQ3BukntV1U3672p7pzsvyfWibbaZdwFD1lq7sqqekeT4dGfqOqq19pU5l7VVqaq3J7lfkltX1XlJXpTkJUneWVV/ku4N+ugkaa19pareme6f2pVJnt5au2ouhW8d7p3kCUm+1B9fmSTPi/aZtx2SvKU/U+ANkryztfaBqvpstMtQec/M322TvLf7npdtkvxna+0jVXVKtM0QPDPJ2/odCd9O8uT0n2/aZn6q6iZJ9kny1JHBPs/mrLX2+ap6d5IvpHutT09yZJKb5XrQNtXaYLs0AwAAQBLdhgEAANgCCK8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwBbmeqcXVWtqn5tzrUcXVWnLmO61l+6bC6q6n59DXcZG/60fviLZry+G1bVYVV191kudxnrPayqvj/D5d2oqg6uqlOq6idV9fOqOquqXtlfT3Czqao1fVs9ZHOuF4DZEV4Btj57JVnT/33AHOvYolXVgUlel+QlrbXDZ7z4G6a7rvXdZ7zcpbwxyb6zWFB/DcgTkxyW7nrpj0ryB0n+JcneST45i/UAsPXYZt4FALDZPS7Jz5J8uf/77+dbzpanqh6X5E1JjmitHTrvemaltXZekvNmtLh/SBe+79la+8rI8E9U1WuT/MmGZq6q1a21dTOqBYDrAXteAbYiVbUqyaOTvD/JUUnuXFX/Z2yaA/vulXetqhOq6mdV9fWqesTINAvdaCfd1vTTPLGqPlVVl1bVD6vqE1W15yJ17VNVX+zX9amq+o2NeG7P7run/qiqLqqq/xrvFl1VJ1XVu6vq8VX1zar6cVV9uKp2nmI9j0jy70le31o7eGzcks95oav0Es/5J/39mye8rjeuqpdV1Xer6hdV9b9V9aCxdZxTVf/cd9k9r6/lHVW13RLP7Trdhkfa+X5V9a6q+mlVfbuq/mKJ5dwkyVOSvG4suCZJWmtXt9beMGE9+1bV+6vqp0le04+bpl2f0j/3dVX1waraaUJ5N6mq1/fLO6+qDq+qG4wt7y79/D/pb++qql/Z1NcFgE0jvAJsXR6Q5LZJ3pHk3UmuSLf3dZL/TBdy/2+Ss5K8YyTkfSFd9+PR26eTfD/JD/tp1qQLeY9O8vh0e/Q+WVV3HFvPLklenm5P3eOS3CbJO6uqpnxuO6cLPA9P8mdJViX5dFXdYmy6eyZ5RpJnpwtYv5nkyGWu48FJ3p7kP5I8fcL4NZnNc35Af//3ufb1/V4/7N1JDkzyj0kemuSUJO+v9Y+PfUy67rlPSfI3SR7Sz7Mx3pDkf9NtCycleW1V3WMD0/9Wkpsk+eiU63lTv56H9X8ny2/XvZI8M8lfpdur+3+SHDdhHS9L8tN03ZjfmuSF/d9Jkj4YfzrJjZM8Id1r/RtJ/mvCNjnt6wLApmitubm5ubltJbd0e1t/mOSG/eMPJjk7SY1Mc2CSluSPR4bdKsmVSZ62yHL/oh//gEXG3yDdoSpfT/LCkeFH9/PtOjJs/379dxoZ1pI8Y4rnuSrJ6nR7MJ84MvykJD9K8ssjw57VL3/1BpZ3v36aluTUJDdYRg0b/ZyT3Kx/fODYMvfuh993bPgnk7xr5PE5Sb6VZJuRYa9KcuESNR+W5PsTnveLR4Ztm+SSdMf6Lracx/bz7b7Ia7LNWG0L63nlJrTrFUluPzLs3v0y9+sfr+kf//vYMs9I8o6Rx/+R5Mz075F+2K5Jrkry4E15Xdzc3NzcNu1mzyvAVqKqbpRuD9F7W2uX94Pfnu5L/b0mzHLNXrPW2g+SXJxuL9j4cn83XTA6tLX28ZHhv15V762qi9J98b8iye5JdhtbxDmttbNGHn+1v192V95+ffeqrpvzD9KFw8vShcDx9Z3SWvvhyOOF9U3qYjruo+n2Kh64SA0r/ZwfmOTCdHset1m4pTsx0niX7E+01q4cW8dtquqGS6xjktFt4Yp0e+I3VOvCHso2Nvz96V6TK5JcUWNnb073Y8p1F7T8dv1Ca+07I3V+Ot02O74ndHxv8FfHnssDk7w3ydUjr+/Z6X4QGH+Np31dANgEwivA1uMPkmyX5ENVtV1//ONJSX6RyV2H1449vjxdV8pr9McUvjvJca21l48Mv3m6L/a3S9eN8z5JfjtdF8vrLGOR9WTCdIuqql369VWSp6bb6/bb6cLLLNd3SJJjkhxZVQ8dq2FzPOdbJ/mVjATA/nZYv96l1lHpzmQ8rUnL2lCt5/f340HuWelek6ctMt9Fow+mbNeLJyzv4iQ7jA1bO/Z4/LncOl036/HX+I5Z3mu87O0WgOk42zDA1mMhoL5rwrjHVNXBrbWrlruwfk/ue5L8IMkfj43eK11w2ae19vWRecaPU5yV/dIdY/nw1trP+nVtk+SWM17P1UmemK4b9TFV9futtU/14zbHc740XTDcf4bLXAmnpdtD+vtJrtkb31r7ZpJU1c0WmW98T+007XqbRYZ9b8LwDbk03Z7XN04YN7Nr4AIwPeEVYCvQh4WHpOsmPH5yoj2SvCLJ/ZN8bIrFvi7JnZLco7X207Fxq/v7X4zU8DvpuiifNsU6lmt1umA52k32MVmB/3OttcurO+PwJ9KdKOn3Wmtfzmyf82J7Yk9Md6Kpn44G5KFprV1WVUcmeXpVvaW19rWNXNQ07fqbVbVLa+3cJKmqe6cLrydPuc4Tk9wlyWmttfEwDcAcCa8AW4eHp9uDdURr7fOjI6rq00men27P7LLCa1U9Pt3e1n9IcsuqGj1m9vQkn0t3Rtc3VNXL0u2RPCzXdiedtY+nO5nPm6vqTenODvvXWb9b50y01n7SX57m00k+0ofUmT3nPiCfnW6P+JeT/DzJF5OckOT4JCdU1UuTfCXJL6W7nuqN27CuOfv8dMebfraqXpPkf9I9j52SPCndMcE/X2IZ07TrxUk+UFWHpQv9L013HOxHpqz7sHSB94NVdVS6va07JdknydGttZOmXB4AM+KYV4Ctw+OSnDUeXJNrTjTzziSP6LsCL8fCyXKen+SzY7cdWmsXpbtczK8keV+6Yx2fluSbm/AcFtVa+1KSJ6e7DM4H0l2m5tHpziy8IlprF6frFrsqXaC8MrN9zk9Ld/zlx9JdDmfHfk/gI9KdNfpZ/Xpfn67L8qcmL2Y+WmuXpbvkz4vTdf99T7p6D093AqS7LXQj3sAypmnXz6brDfCqdJfZ+XI2ont1a+0b6U5gdlm6Xgof7mv+RVZo+wVgeUqPGABgS1ZVJ6W7xM+jlpoWgC2XPa8AAAAMnvAKAADA4Ok2DAAAwODZ8woAAMDgCa8AAAAMnvAKAADA4AmvAAAADJ7wCgAAwOAJrwAAAAze/we9cx7cUPO2BgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,10))\n",
    "ax.set_title(\"Zeit, bis gültige LP-Lösung gefunden ist für 2 Szenarien\", fontsize=20)\n",
    "ax.set_xlabel(\"Anzahl an Kanten in Graphen\", fontsize=15)\n",
    "ax.set_ylabel(\"Benötigte Zeit [$s$]\", fontsize=15)\n",
    "ax.errorbar(e2, m_loop2, s_loop2, fmt='o', capsize=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "06f3c65b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ErrorbarContainer object of 3 artists>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16,10))\n",
    "ax.set_title(\"Zeit, bis gültige LP-Lösung gefunden ist für 10 Szenarien\", fontsize=20)\n",
    "ax.set_xlabel(\"Anzahl an Kanten in Graphen\", fontsize=15)\n",
    "ax.set_ylabel(\"Benötigte Zeit [$s$]\", fontsize=15)\n",
    "ax.errorbar(e10, m_loop10, s_loop10, fmt='o', capsize=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9eddfe6f",
   "metadata": {},
   "source": [
    "# Jetzt will ich rausfinden, welcher Teil vom LP-Alg so lange dauert"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e8e9cb17",
   "metadata": {},
   "outputs": [],
   "source": [
    "pt = r\"D:\\Uni\\Masterarbeit\\Daten\\LP_Tracking\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "125acc74",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_tracking_files(p):\n",
    "    \"\"\"\n",
    "    p ist pfad zu einer simulation_x\n",
    "    \n",
    "    \"\"\"\n",
    "    pt = os.path.join(p, \"Tracking\")\n",
    "    pt_opt = os.path.join(pt, \"opt\")\n",
    "#     print(pt_opt)\n",
    "    \n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    df['counters'] = np.loadtxt(os.path.join(pt, \"counters.txt\"), dtype=int)\n",
    "    df['setup'] = np.loadtxt(os.path.join(pt, \"setup_zeiten_s.txt\"), dtype=int)\n",
    "    df['loop'] = np.loadtxt(os.path.join(pt, \"loop_zeiten_s.txt\"), dtype=int)\n",
    "    df['total'] = np.loadtxt(os.path.join(pt, \"total.txt\")) / 1000\n",
    "    \n",
    "    opt = [np.loadtxt(os.path.join(pt_opt, i)) for i in sorted(os.listdir(pt_opt), key=lambda x: int(x.split(\"_\")[0]))]\n",
    "    \n",
    "    sums = [sum(i)/1000 for i in opt]\n",
    "    \n",
    "    df['Summe Opt'] = sums\n",
    "#     d_f = {'counters': counters, 'setup_zeiten': setup, 'loop_zeiten': loop, 'total': total, 'opt': opt}\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "41e4a31c",
   "metadata": {},
   "outputs": [],
   "source": [
    "d50a = load_tracking_files(r\"D:\\Uni\\Masterarbeit\\Daten\\LP_Tracking\\TimeTest_50_nodes_10_scenarios\\TreePlusP_0.000000_p_50_nodes_10_RandomScenarioCreator_RandomTestCreator_0.000000_10.000000\\simulation_0\")\n",
    "# d80 = load_tracking_files(r\"D:\\Uni\\Masterarbeit\\Daten\\LP_Tracking\\TimeTest_80_nodes_10_scenarios\\TreePlusP_0.000000_p_80_nodes_10_RandomScenarioCreator_RandomTestCreator_0.000000_10.000000\\simulation_1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "515739c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.41786803918775584"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(d50a['Summe Opt'] / d50a['total']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "4309165d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2664.998"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d50.mean().counters"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc848576",
   "metadata": {},
   "source": [
    "## Auswertung\n",
    "\n",
    "Es kommt selten mal vor, dass die komplette (totale) Laufzeit des LP minimal länger war, als die Zeit, die das while-loop gebraucht hat. Das kommt bei 80 Knoten häufiger vor als bei 50.\n",
    "\n",
    "### Wie viel Prozent der Gesamtlaufzeit machen die Gurobi-Optimierungen aus\n",
    "\n",
    "Ein anderer Teil der Zeit kosten kann ist das hinzufügen von neuen Bedingungen.\n",
    "\n",
    "Wann werden wie viele Bedingungen im Durchschnitt hinzugefügt?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39e8251e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ich muss für alle Simulationen pro Konfiguration ein Dataframe ueber alle simulation_x Ordner machen, daraus dann\n",
    "# die Anteile berechnen und das dann plotten"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "78fbd05c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_tracking_files(konfig_path):\n",
    "    \"\"\"\n",
    "    Ist dafuer da, fuer eine Konfiguration ueber alle Simulationen zu gehen und die Trackingdaten in ein einziges\n",
    "    Dataframe zu packen\n",
    "    \"\"\"\n",
    "    \n",
    "    # muss erstmal rausfinden, welche Simulationen alle gemacht wurden\n",
    "    sims = os.listdir(konfig_path)\n",
    "    \n",
    "    # erstes Dataframe von simulation_0\n",
    "    df = load_tracking_files(os.path.join(konfig_path, sims[0]))\n",
    "    \n",
    "    # die restlichen simulation_x Ordner einlesen und an das DataFrame dranpacken\n",
    "    for sim in sims[1:]:\n",
    "\n",
    "        df_sim = load_tracking_files(os.path.join(konfig_path, sim))\n",
    "        df = pd.concat([df, df_sim], ignore_index=True)\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "ff63a972",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_konfigs(ueber_path):\n",
    "    \"\"\"\n",
    "    Ist dafuer da, fuer einen Ueberordner alle Trackingdaten der Konfigurationen (Variable ist hier p) in eine plotbare Form\n",
    "    zu bringen\n",
    "    \n",
    "    dazu gebe ich ein DataFrame zurueck, wo \n",
    "    \"\"\"\n",
    "    \n",
    "    # jetzt alle Ergebnisse einlesen\n",
    "    konfigs = os.listdir(ueber_path)\n",
    "    \n",
    "    # dictionary, was mir fuer die verschiedenen Simulationen den Index zum relevanten Parameter gibt\n",
    "    # Fuer TreePlusP, ist hier die Wahrscheinlichkeit p relevant\n",
    "    d = {\"TreePlusP\": 1}\n",
    "    ps = [float(k.split(\"_\")[d[k.split(\"_\")[0]]]) for k in konfigs]\n",
    "    dfs = [read_tracking_files(os.path.join(ueber_path, k)) for k in konfigs]\n",
    "    \n",
    "    df_res = pd.DataFrame()\n",
    "    df_res['p'] = ps\n",
    "    \n",
    "    # jetzt Daten verarbeiten\n",
    "    # mittlere Anzahl an Iterationen\n",
    "    mean_its = [df.mean().counters for df in dfs]\n",
    "    df_res['m_iterations'] = mean_its\n",
    "    \n",
    "    # mittlerer totale Laufzeit in s\n",
    "    df_res['m_total'] = [df.mean().total for df in dfs]\n",
    "    \n",
    "    # mittlerer Anteil von den Gurobioptimierungsschritten an Gesamtlaufzeit\n",
    "    df_res['anteil_opt'] = [(df['Summe Opt'] / df['total']).mean() for df in dfs]\n",
    "    \n",
    "    return df_res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "ff86e312",
   "metadata": {},
   "outputs": [],
   "source": [
    "d = get_konfigs(r\"D:\\Uni\\Masterarbeit\\Daten\\LP_Tracking\\TimeTest_10_nodes_10_scenarios\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "004b18bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>p</th>\n",
       "      <th>m_iterations</th>\n",
       "      <th>m_total</th>\n",
       "      <th>anteil_opt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00</td>\n",
       "      <td>147.559</td>\n",
       "      <td>0.066372</td>\n",
       "      <td>0.221130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.05</td>\n",
       "      <td>147.228</td>\n",
       "      <td>0.075978</td>\n",
       "      <td>0.246673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.10</td>\n",
       "      <td>152.228</td>\n",
       "      <td>0.085792</td>\n",
       "      <td>0.266769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.15</td>\n",
       "      <td>155.932</td>\n",
       "      <td>0.093068</td>\n",
       "      <td>0.279953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.20</td>\n",
       "      <td>158.496</td>\n",
       "      <td>0.099335</td>\n",
       "      <td>0.291673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.25</td>\n",
       "      <td>163.798</td>\n",
       "      <td>0.106839</td>\n",
       "      <td>0.300531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.30</td>\n",
       "      <td>163.808</td>\n",
       "      <td>0.111663</td>\n",
       "      <td>0.307334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.35</td>\n",
       "      <td>166.034</td>\n",
       "      <td>0.116273</td>\n",
       "      <td>0.312943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.40</td>\n",
       "      <td>168.080</td>\n",
       "      <td>0.121634</td>\n",
       "      <td>0.318625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.45</td>\n",
       "      <td>167.364</td>\n",
       "      <td>0.124425</td>\n",
       "      <td>0.322675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.50</td>\n",
       "      <td>169.956</td>\n",
       "      <td>0.130830</td>\n",
       "      <td>0.327354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.60</td>\n",
       "      <td>169.302</td>\n",
       "      <td>0.137213</td>\n",
       "      <td>0.331295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.70</td>\n",
       "      <td>170.328</td>\n",
       "      <td>0.144998</td>\n",
       "      <td>0.336734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.80</td>\n",
       "      <td>172.218</td>\n",
       "      <td>0.153159</td>\n",
       "      <td>0.342154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.90</td>\n",
       "      <td>171.836</td>\n",
       "      <td>0.159276</td>\n",
       "      <td>0.344965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1.00</td>\n",
       "      <td>173.708</td>\n",
       "      <td>0.167786</td>\n",
       "      <td>0.348411</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       p  m_iterations   m_total  anteil_opt\n",
       "0   0.00       147.559  0.066372    0.221130\n",
       "1   0.05       147.228  0.075978    0.246673\n",
       "2   0.10       152.228  0.085792    0.266769\n",
       "3   0.15       155.932  0.093068    0.279953\n",
       "4   0.20       158.496  0.099335    0.291673\n",
       "5   0.25       163.798  0.106839    0.300531\n",
       "6   0.30       163.808  0.111663    0.307334\n",
       "7   0.35       166.034  0.116273    0.312943\n",
       "8   0.40       168.080  0.121634    0.318625\n",
       "9   0.45       167.364  0.124425    0.322675\n",
       "10  0.50       169.956  0.130830    0.327354\n",
       "11  0.60       169.302  0.137213    0.331295\n",
       "12  0.70       170.328  0.144998    0.336734\n",
       "13  0.80       172.218  0.153159    0.342154\n",
       "14  0.90       171.836  0.159276    0.344965\n",
       "15  1.00       173.708  0.167786    0.348411"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a58ad88c",
   "metadata": {},
   "source": [
    "## Das jetzt fuer alle Simulationen machen und plotten"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "5ea36c83",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Daten einlesen (extra, weil dauert lange, also mehrere Minuten)\n",
    "p = r\"D:\\Uni\\Masterarbeit\\Daten\\LP_Tracking\"\n",
    "\n",
    "data = {s: get_konfigs(os.path.join(p, s)) for s in os.listdir(p)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "96883372",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1500705b688>"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotten\n",
    "fig, ax = plt.subplots(figsize=(16, 10))\n",
    "\n",
    "for s in sorted(data, key=lambda x: int(x.split(\"_\")[1])):\n",
    "#     if not \"50\" in s:\n",
    "    ax.scatter(data[s]['p'], data[s]['anteil_opt'], label=s)\n",
    "ax.set_ylim([0,1])\n",
    "ax.set_title(\"Anteil Opt an Gesamtlaufzeit\")\n",
    "ax.set_xlabel(\"Wahrscheinlichkeit p eine Kante zu einem Baum hinzuzufügen\")\n",
    "ax.set_ylabel(\"Anteil der Gurobi Optimierungsschritte an der Gesamtlaufzeit des LP-Algorithmus\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34bc5c87",
   "metadata": {},
   "source": [
    "# Auswertung\n",
    "Der Anteil der Gurobi-Optimierungsschritte an der Gesamtzeit wächst mit höherer Kantenanzahl und ist für Graphen mit mehr Knoten größer. Also: Je mehr Kanten und v.A. je mehr Knoten es gibt, desto höher wird der Anteil der Optimierungsschritte an der Gesamtlaufzeit des LP-Algorithmus. Da kann ich also für größere Problemstellungen nicht mehr viel optimieren, wenn ich bei Gruobi bleiben will und das will ich. Was auffällt ist, dass für kleine p der Anteil bei 50 Knoten größer ist als bei 60. Keine Ahnung woran das liegt. Denn es werden bei 60 Knoten durchschnittlich mehr Constraints benötigt und insgesammt braucht der Algorithmus auch länger bei 60 Knoten. Aus irgendeinem Grund ist der Gurobi-Alg. da aber anscheinend schneller. \n",
    "\n",
    "Der Rest der Laufzeit ist dann der Teil, wo ich schaue, ob für alle Szenarien die Min-Cut Bedingung erfüllt ist und das Hinzufügen neuer Bedingungen, falls die Bedingung nicht erfüllt ist."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f2698e48",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'plt' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_19632/1919827998.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# plotten\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mfig\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0max\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msubplots\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m16\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m10\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[1;32min\u001b[0m \u001b[0msorted\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"_\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;31m#     if not \"50\" in s:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'plt' is not defined"
     ]
    }
   ],
   "source": [
    "# plotten\n",
    "fig, ax = plt.subplots(figsize=(16, 10))\n",
    "\n",
    "for s in sorted(data, key=lambda x: int(x.split(\"_\")[1])):\n",
    "#     if not \"50\" in s:\n",
    "    ax.scatter(data[s]['p'], data[s]['m_iterations'], label=s)\n",
    "ax.set_title(\"Durchschnittliche Anzahl an hinzugefügten Constraints\")\n",
    "ax.set_ylabel(\"Anzahl Constraints\")\n",
    "ax.set_xlabel(\"p\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "2f697d19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1500796e908>"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotten\n",
    "fig, ax = plt.subplots(figsize=(16, 10))\n",
    "\n",
    "for s in sorted(data, key=lambda x: int(x.split(\"_\")[1])):\n",
    "#     if not \"50\" in s:\n",
    "    ax.scatter(data[s]['p'], data[s]['m_total'], label=s)\n",
    "ax.set_title(\"durchschnittliche Gesamtlaufzeit\")\n",
    "ax.set_xlabel(\"Wahrscheinlichkeit p eine Kante zu einem Baum hinzuzufügen\")\n",
    "ax.set_ylabel(\"Zeit [s]\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69940fed",
   "metadata": {},
   "source": [
    "## 2 Szenarien"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "bee60c62",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Daten einlesen (extra, weil dauert lange, also mehrere Minuten)\n",
    "p2 = r\"D:\\Uni\\Masterarbeit\\Daten\\LP_Tracking\\2_scen\"\n",
    "\n",
    "data2 = {s: get_konfigs(os.path.join(p2, s)) for s in os.listdir(p2)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "5e83ba8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1500275c188>"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotten\n",
    "fig, ax = plt.subplots(figsize=(16, 10))\n",
    "\n",
    "for s in sorted(data2, key=lambda x: int(x.split(\"_\")[1])):\n",
    "#     if not \"50\" in s:\n",
    "    ax.scatter(data2[s]['p'], data2[s]['anteil_opt'], label=s)\n",
    "ax.set_ylim([0,1])\n",
    "ax.set_title(\"Anteil Opt an Gesamtlaufzeit\")\n",
    "ax.set_xlabel(\"Wahrscheinlichkeit p eine Kante zu einem Baum hinzuzufügen\")\n",
    "ax.set_ylabel(\"Anteil der Gurobi Optimierungsschritte an der Gesamtlaufzeit des LP-Algorithmus\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99404302",
   "metadata": {},
   "source": [
    "Auch für nur 2 Szenarien machen die Gurobi-Optimierungsschritte einen großen Teil der Gesamtlaufzeit aus."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "3a1d6c9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x15000bd12c8>"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotten\n",
    "fig, ax = plt.subplots(figsize=(16, 10))\n",
    "\n",
    "for s in sorted(data2, key=lambda x: int(x.split(\"_\")[1])):\n",
    "#     if not \"50\" in s:\n",
    "    ax.scatter(data2[s]['p'], data2[s]['m_iterations'], label=s)\n",
    "ax.set_title(\"Durchschnittliche Anzahl an hinzugefügten Constraints\")\n",
    "ax.set_xlabel(\"Anzahl Constraints\")\n",
    "ax.set_ylabel(\"Anteil der Gurobi Optimierungsschritte an der Gesamtlaufzeit des LP-Algorithmus\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "125ed42d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1500643af08>"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotten\n",
    "fig, ax = plt.subplots(figsize=(16, 10))\n",
    "\n",
    "for s in sorted(data2, key=lambda x: int(x.split(\"_\")[1])):\n",
    "#     if not \"50\" in s:\n",
    "    ax.scatter(data2[s]['p'], data2[s]['m_total'], label=s)\n",
    "ax.set_title(\"durchschnittliche Gesamtlaufzeit\")\n",
    "ax.set_xlabel(\"Wahrscheinlichkeit p eine Kante zu einem Baum hinzuzufügen\")\n",
    "ax.set_ylabel(\"Zeit [s]\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c1bcf67",
   "metadata": {},
   "source": [
    "Für bis zu 50 Knoten wächst die Gesamtlaufzeit für den LP-Alg nicht so schnell für größere p an, aber für 80 dann schon schneller. Ist aber auch verständlich, weil mit mehr Knoten auch immer mehr potentielle Kanten dazu kommen. Vielleicht gibt es da eine gewissen Knotenanzahl ab der das stark steigt?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98b8bab7",
   "metadata": {},
   "source": [
    "# Und jetzt?\n",
    "Ich will nen Phasenübergang sehen!"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}