GN_Algorithm.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import operator\n",
    "import networkx as nx\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def graph():    \n",
    "    import graph\n",
    "    Graph = graph.H\n",
    "    return Graph\n",
    "G= graph()\n",
    "#G=nx.karate_club_graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "edge: (0, 31) None\n",
      "R.components 1\n",
      "edge: (0, 2) None\n",
      "R.components 1\n",
      "edge: (0, 8) None\n",
      "R.components 1\n",
      "edge: (13, 33) None\n",
      "R.components 1\n",
      "edge: (19, 33) None\n",
      "R.components 1\n",
      "edge: (2, 32) None\n",
      "R.components 1\n",
      "edge: (1, 30) None\n",
      "R.components 1\n",
      "edge: (1, 2) None\n",
      "R.components 1\n",
      "edge: (2, 3) None\n",
      "R.components 1\n",
      "edge: (2, 13) None\n",
      "R.components 1\n",
      "edge: (2, 7) None\n",
      "R.components 2\n",
      "edge: (9, 33) None\n",
      "R.components 2\n",
      "edge: (27, 33) None\n",
      "R.components 2\n",
      "edge: (2, 9) None\n",
      "R.components 3\n",
      "edge: (0, 6) None\n",
      "R.components 3\n",
      "edge: (0, 5) None\n",
      "R.components 3\n",
      "edge: (0, 10) None\n",
      "R.components 3\n",
      "edge: (0, 4) None\n",
      "R.components 4\n",
      "edge: (31, 33) None\n",
      "R.components 4\n",
      "edge: (31, 32) None\n",
      "R.components 4\n",
      "edge: (28, 33) None\n",
      "R.components 4\n",
      "edge: (23, 25) None\n",
      "R.components 4\n",
      "edge: (23, 27) None\n",
      "R.components 4\n",
      "edge: (2, 8) None\n",
      "R.components 5\n",
      "edge: (26, 33) None\n",
      "R.components 5\n",
      "edge: (26, 29) None\n",
      "R.components 6\n",
      "edge: (0, 11) None\n",
      "R.components 7\n",
      "edge: (0, 12) None\n",
      "R.components 7\n",
      "edge: (3, 12) None\n",
      "R.components 8\n",
      "edge: (22, 33) None\n",
      "R.components 8\n",
      "edge: (22, 32) None\n",
      "R.components 9\n",
      "edge: (28, 31) None\n",
      "R.components 9\n",
      "edge: (24, 27) None\n",
      "R.components 10\n",
      "edge: (20, 33) None\n",
      "R.components 10\n",
      "edge: (20, 32) None\n",
      "R.components 11\n",
      "edge: (18, 33) None\n",
      "R.components 11\n",
      "edge: (18, 32) None\n",
      "R.components 12\n",
      "edge: (15, 33) None\n",
      "R.components 12\n",
      "edge: (15, 32) None\n",
      "R.components 13\n",
      "edge: (1, 21) None\n",
      "R.components 13\n",
      "edge: (0, 21) None\n",
      "R.components 14\n",
      "edge: (14, 33) None\n",
      "R.components 14\n",
      "edge: (14, 32) None\n",
      "R.components 15\n",
      "edge: (5, 10) None\n",
      "R.components 15\n",
      "edge: (4, 6) None\n",
      "R.components 16\n",
      "edge: (1, 19) None\n",
      "R.components 16\n",
      "edge: (0, 19) None\n",
      "R.components 17\n",
      "edge: (1, 17) None\n",
      "R.components 17\n",
      "edge: (0, 17) None\n",
      "R.components 18\n",
      "edge: (30, 33) None\n",
      "R.components 18\n",
      "edge: (30, 32) None\n",
      "R.components 18\n",
      "edge: (8, 30) None\n",
      "R.components 19\n",
      "edge: (8, 33) None\n",
      "R.components 19\n",
      "edge: (8, 32) None\n",
      "R.components 20\n",
      "edge: (2, 28) None\n",
      "R.components 21\n",
      "edge: (3, 13) None\n",
      "R.components 21\n",
      "edge: (1, 13) None\n",
      "R.components 21\n",
      "edge: (0, 13) None\n",
      "R.components 22\n",
      "edge: (32, 33) None\n",
      "R.components 22\n",
      "edge: (29, 33) None\n",
      "R.components 22\n",
      "edge: (23, 33) None\n",
      "R.components 23\n",
      "edge: (29, 32) None\n",
      "R.components 23\n",
      "edge: (23, 32) None\n",
      "R.components 24\n",
      "edge: (25, 31) None\n",
      "R.components 24\n",
      "edge: (24, 31) None\n",
      "R.components 25\n",
      "edge: (24, 25) None\n",
      "R.components 26\n",
      "edge: (23, 29) None\n",
      "R.components 27\n",
      "edge: (6, 16) None\n",
      "R.components 27\n",
      "edge: (5, 16) None\n",
      "R.components 28\n",
      "edge: (5, 6) None\n",
      "R.components 29\n",
      "edge: (4, 10) None\n",
      "R.components 30\n",
      "edge: (3, 7) None\n",
      "R.components 30\n",
      "edge: (1, 7) None\n",
      "R.components 30\n",
      "edge: (0, 7) None\n",
      "R.components 31\n",
      "edge: (2, 27) None\n",
      "R.components 32\n",
      "edge: (1, 3) None\n",
      "R.components 32\n",
      "edge: (0, 3) None\n",
      "R.components 33\n",
      "edge: (0, 1) None\n",
      "R.components 34\n"
     ]
    }
   ],
   "source": [
    "sorted_bc=[1]\n",
    "j=[]\n",
    "actual_num_components=1\n",
    "while not sorted_bc==[]:\n",
    "    d_edges=nx.edge_betweenness_centrality(G)\n",
    "    sorted_bc = sorted(d_edges.items(), key=operator.itemgetter(1))\n",
    "    e=sorted_bc.pop()\n",
    "    h=list(e[0])    \n",
    "    print (\"edge:\", e[0],\n",
    "    G.remove_edge(*e[0]))\n",
    "    num_comp = nx.number_connected_components(G)\n",
    "    k = h, num_comp\n",
    "    j.append(k) \n",
    "    print (\"R.components\", num_comp)\n",
    "    \n",
    "    if num_comp>actual_num_components:\n",
    "           actual_num_components=num_comp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "    .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>edges</th>\n",
       "      <th>l_comp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[0, 31]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[0, 2]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[0, 8]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[13, 33]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[19, 33]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>[2, 32]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>[1, 30]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>[1, 2]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>[2, 3]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>[2, 13]</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>[2, 7]</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>[9, 33]</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>[27, 33]</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>[2, 9]</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>[0, 6]</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>[0, 5]</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>[0, 10]</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>[0, 4]</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>[31, 33]</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>[31, 32]</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>[28, 33]</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>[23, 25]</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>[23, 27]</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>[2, 8]</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>[26, 33]</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>[26, 29]</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>[0, 11]</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>[0, 12]</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>[3, 12]</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>[22, 33]</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>[0, 17]</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>[30, 33]</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>[30, 32]</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>[8, 30]</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>[8, 33]</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>[8, 32]</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>[2, 28]</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>[3, 13]</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>[1, 13]</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>[0, 13]</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>[32, 33]</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>[29, 33]</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>[23, 33]</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>[29, 32]</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>[23, 32]</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>[25, 31]</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>[24, 31]</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>[24, 25]</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>[23, 29]</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>[6, 16]</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>[5, 16]</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>[5, 6]</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>[4, 10]</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>[3, 7]</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>[1, 7]</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>[0, 7]</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>[2, 27]</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>[1, 3]</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>[0, 3]</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>[0, 1]</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>78 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       edges  l_comp\n",
       "0    [0, 31]       1\n",
       "1     [0, 2]       1\n",
       "2     [0, 8]       1\n",
       "3   [13, 33]       1\n",
       "4   [19, 33]       1\n",
       "5    [2, 32]       1\n",
       "6    [1, 30]       1\n",
       "7     [1, 2]       1\n",
       "8     [2, 3]       1\n",
       "9    [2, 13]       1\n",
       "10    [2, 7]       2\n",
       "11   [9, 33]       2\n",
       "12  [27, 33]       2\n",
       "13    [2, 9]       3\n",
       "14    [0, 6]       3\n",
       "15    [0, 5]       3\n",
       "16   [0, 10]       3\n",
       "17    [0, 4]       4\n",
       "18  [31, 33]       4\n",
       "19  [31, 32]       4\n",
       "20  [28, 33]       4\n",
       "21  [23, 25]       4\n",
       "22  [23, 27]       4\n",
       "23    [2, 8]       5\n",
       "24  [26, 33]       5\n",
       "25  [26, 29]       6\n",
       "26   [0, 11]       7\n",
       "27   [0, 12]       7\n",
       "28   [3, 12]       8\n",
       "29  [22, 33]       8\n",
       "..       ...     ...\n",
       "48   [0, 17]      18\n",
       "49  [30, 33]      18\n",
       "50  [30, 32]      18\n",
       "51   [8, 30]      19\n",
       "52   [8, 33]      19\n",
       "53   [8, 32]      20\n",
       "54   [2, 28]      21\n",
       "55   [3, 13]      21\n",
       "56   [1, 13]      21\n",
       "57   [0, 13]      22\n",
       "58  [32, 33]      22\n",
       "59  [29, 33]      22\n",
       "60  [23, 33]      23\n",
       "61  [29, 32]      23\n",
       "62  [23, 32]      24\n",
       "63  [25, 31]      24\n",
       "64  [24, 31]      25\n",
       "65  [24, 25]      26\n",
       "66  [23, 29]      27\n",
       "67   [6, 16]      27\n",
       "68   [5, 16]      28\n",
       "69    [5, 6]      29\n",
       "70   [4, 10]      30\n",
       "71    [3, 7]      30\n",
       "72    [1, 7]      30\n",
       "73    [0, 7]      31\n",
       "74   [2, 27]      32\n",
       "75    [1, 3]      32\n",
       "76    [0, 3]      33\n",
       "77    [0, 1]      34\n",
       "\n",
       "[78 rows x 2 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TPN = pd.DataFrame(j, columns = ('edges','l_comp'))\n",
    "TPN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(TPN.l_comp, 'g-+')\n",
    "#plt.plot(eff_table.Density, 'g-o')\n",
    "plt.legend([\"Efficiency\"])\n",
    "plt.xlabel(\"nodes\")\n",
    "plt.ylabel(\"Efficiency\")\n",
    "plt.savefig(\"result/email_eff1.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}