network_ana

Complex Network Anlysis
git clone git://popovic.xyz/network_ana.git
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main.ipynb (141543B)


      1 {
      2  "cells": [
      3   {
      4    "cell_type": "code",
      5    "execution_count": 1,
      6    "id": "e1d43e31",
      7    "metadata": {},
      8    "outputs": [],
      9    "source": [
     10     "import numpy as np\n",
     11     "import networkx as nx\n",
     12     "import itertools\n",
     13     "import random\n",
     14     "import matplotlib.pyplot as plt"
     15    ]
     16   },
     17   {
     18    "cell_type": "code",
     19    "execution_count": 50,
     20    "id": "974f553a",
     21    "metadata": {},
     22    "outputs": [],
     23    "source": [
     24     "class Attack:\n",
     25     "    def __init__(self, G, steps=25):\n",
     26     "        self.G = G\n",
     27     "        self.steps = steps\n",
     28     "        self.N = G.number_of_nodes()\n",
     29     "        self.M = self.N // self.steps\n",
     30     "        self.num_nodes_removed = range(0, self.N, self.M)\n",
     31     "        \n",
     32     "    def random(self):\n",
     33     "        C = self.G.copy()\n",
     34     "        random_attack_core_proportions = []\n",
     35     "        for nodes_removed in self.num_nodes_removed:\n",
     36     "            # Measure the relative size of the network core\n",
     37     "            core = sorted(nx.connected_components(C), key = len, reverse=True)[0] # mistake in notebook 6\n",
     38     "            core_proportion = len(core) / self.N\n",
     39     "            random_attack_core_proportions.append(core_proportion)\n",
     40     "\n",
     41     "            # If there are more than M nodes, select M nodes at random and remove them\n",
     42     "            if C.number_of_nodes() > self.M:\n",
     43     "                nodes_to_remove = random.sample(list(C.nodes), self.M)\n",
     44     "                C.remove_nodes_from(nodes_to_remove)\n",
     45     "        return self.num_nodes_removed, random_attack_core_proportions\n",
     46     "\n",
     47     "    def betweenness(self):\n",
     48     "        C = self.G.copy()\n",
     49     "        random_attack_core_proportions = []\n",
     50     "        for nodes_removed in self.num_nodes_removed:\n",
     51     "            # Measure the relative size of the network core\n",
     52     "            core = sorted(nx.connected_components(C), key = len, reverse=True)[0] # mistake in notebook 6\n",
     53     "            core_proportion = len(core) / self.N\n",
     54     "            random_attack_core_proportions.append(core_proportion)\n",
     55     "\n",
     56     "            # If there are more than M nodes, select M nodes at random and remove them\n",
     57     "            if C.number_of_nodes() > self.M:\n",
     58     "                betweenness = nx.centrality.betweenness_centrality(C)\n",
     59     "                nodes_sorted_by_betweenness= sorted(C.nodes, key=betweenness.get, reverse=True)\n",
     60     "                nodes_to_remove = nodes_sorted_by_betweenness[:self.M]\n",
     61     "                C.remove_nodes_from(nodes_to_remove)\n",
     62     "        return self.num_nodes_removed, random_attack_core_proportions \n",
     63     "\n",
     64     "    def degree(self):\n",
     65     "        C = self.G.copy()\n",
     66     "        random_attack_core_proportions = []\n",
     67     "        for nodes_removed in self.num_nodes_removed:\n",
     68     "            # Measure the relative size of the network core\n",
     69     "            core = sorted(nx.connected_components(C), key = len, reverse=True)[0] # mistake in notebook 6\n",
     70     "            core_proportion = len(core) / self.N\n",
     71     "            random_attack_core_proportions.append(core_proportion)\n",
     72     "\n",
     73     "            # If there are more than M nodes, select M nodes at random and remove them\n",
     74     "            if C.number_of_nodes() > self.M:\n",
     75     "                nodes_sorted_by_degree = sorted(C.nodes, key=C.degree, reverse=True)\n",
     76     "                nodes_to_remove = nodes_sorted_by_degree[:self.M]\n",
     77     "                C.remove_nodes_from(nodes_to_remove)\n",
     78     "        return self.num_nodes_removed, random_attack_core_proportions \n",
     79     "\n",
     80     "    def closeness(self):\n",
     81     "        C = self.G.copy()\n",
     82     "        random_attack_core_proportions = []\n",
     83     "        for nodes_removed in self.num_nodes_removed:\n",
     84     "            # Measure the relative size of the network core\n",
     85     "            core = sorted(nx.connected_components(C), key = len, reverse=True)[0] # mistake in notebook 6\n",
     86     "            core_proportion = len(core) / self.N\n",
     87     "            random_attack_core_proportions.append(core_proportion)\n",
     88     "\n",
     89     "            # If there are more than M nodes, select M nodes at random and remove them\n",
     90     "            if C.number_of_nodes() > self.M:\n",
     91     "                closeness = nx.centrality.closeness_centrality(C)\n",
     92     "                nodes_sorted_by_closeness = sorted(C.nodes, key=closeness.get, reverse=True)\n",
     93     "                nodes_to_remove = nodes_sorted_by_closeness[:self.M]\n",
     94     "                C.remove_nodes_from(nodes_to_remove)\n",
     95     "        return self.num_nodes_removed, random_attack_core_proportions "
     96    ]
     97   },
     98   {
     99    "cell_type": "markdown",
    100    "id": "dc8fce39",
    101    "metadata": {},
    102    "source": [
    103     "# Exercise 7a) Barabasi-Albert-Model"
    104    ]
    105   },
    106   {
    107    "cell_type": "code",
    108    "execution_count": 82,
    109    "id": "5d87dc35",
    110    "metadata": {},
    111    "outputs": [
    112     {
    113      "data": {
    114       "text/plain": [
    115        "Text(0.5, 0.98, 'Random Attack on Barabasi Albert Model (n, m)')"
    116       ]
    117      },
    118      "execution_count": 82,
    119      "metadata": {},
    120      "output_type": "execute_result"
    121     },
    122     {
    123      "data": {
    124       "image/png": 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\n",
    125       "text/plain": [
    126        "<Figure size 720x576 with 4 Axes>"
    127       ]
    128      },
    129      "metadata": {
    130       "needs_background": "light"
    131      },
    132      "output_type": "display_data"
    133     }
    134    ],
    135    "source": [
    136     "ns = [100, 1000]\n",
    137     "ms = [2, 5]\n",
    138     "fig, ax = plt.subplots(2, 2, figsize=(10, 8))\n",
    139     "for i, n in enumerate(ns):\n",
    140     "    for j, m in enumerate(ms):\n",
    141     "        marker = '.'\n",
    142     "        if j == 1:\n",
    143     "            marker='o'\n",
    144     "        G = nx.generators.random_graphs.barabasi_albert_graph(n, m)\n",
    145     "        attack = Attack(G)\n",
    146     "        ax[i][j].plot(*attack.random(), marker=marker, label=f\"(n, m) = ({n}, {m})\")\n",
    147     "        ax[i][j].set_xlabel(\"Number of Nodes removed\")\n",
    148     "        ax[i][j].set_ylabel(\"Porportion of nodes in Core\")\n",
    149     "        ax[i][j].legend(loc=\"best\")\n",
    150     "fig.suptitle(\"Random Attack on Barabasi Albert Model (n, m)\", fontsize=16)"
    151    ]
    152   },
    153   {
    154    "cell_type": "markdown",
    155    "id": "d434d77e",
    156    "metadata": {},
    157    "source": [
    158     "# Exercise 7b)"
    159    ]
    160   },
    161   {
    162    "cell_type": "code",
    163    "execution_count": 83,
    164    "id": "553a7f9a",
    165    "metadata": {},
    166    "outputs": [
    167     {
    168      "name": "stdout",
    169      "output_type": "stream",
    170      "text": [
    171       "Graph with 2018 nodes and 2930 edges\n"
    172      ]
    173     },
    174     {
    175      "data": {
    176       "text/plain": [
    177        "Text(0.5, 1.0, 'Random Attack on protein.elist')"
    178       ]
    179      },
    180      "execution_count": 83,
    181      "metadata": {},
    182      "output_type": "execute_result"
    183     },
    184     {
    185      "data": {
    186       "image/png": 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\n",
    187       "text/plain": [
    188        "<Figure size 432x288 with 1 Axes>"
    189       ]
    190      },
    191      "metadata": {
    192       "needs_background": "light"
    193      },
    194      "output_type": "display_data"
    195     }
    196    ],
    197    "source": [
    198     "path = './../../../network_course/data/'\n",
    199     "G = nx.read_edgelist(path + 'protein.edgelist.txt', nodetype=int)\n",
    200     "print(nx.info(G))\n",
    201     "attack = Attack(G)\n",
    202     "\n",
    203     "x_r, y_r = attack.random()\n",
    204     "plt.plot(x_r, y_r, marker='o', label=\"protein.elist\")\n",
    205     "plt.xlabel(\"Number of nodes removed\")\n",
    206     "plt.ylabel(\"Porportion of nodes in core\")\n",
    207     "plt.legend(loc='best')\n",
    208     "plt.title(\"Random Attack on protein.elist\", fontsize=16)"
    209    ]
    210   },
    211   {
    212    "cell_type": "markdown",
    213    "id": "af3a7c1d",
    214    "metadata": {},
    215    "source": [
    216     "# Exercise 7c)"
    217    ]
    218   },
    219   {
    220    "cell_type": "code",
    221    "execution_count": 104,
    222    "id": "e7c3e3c7",
    223    "metadata": {},
    224    "outputs": [
    225     {
    226      "data": {
    227       "text/plain": [
    228        "Text(0.5, 0.98, 'Random Attack on Erdos-Renyi Network (n, p)')"
    229       ]
    230      },
    231      "execution_count": 104,
    232      "metadata": {},
    233      "output_type": "execute_result"
    234     },
    235     {
    236      "data": {
    237       "image/png": 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\n",
    238       "text/plain": [
    239        "<Figure size 720x576 with 4 Axes>"
    240       ]
    241      },
    242      "metadata": {
    243       "needs_background": "light"
    244      },
    245      "output_type": "display_data"
    246     }
    247    ],
    248    "source": [
    249     "ns = [100, 1000]\n",
    250     "ps = [0.1, 0.5]\n",
    251     "\n",
    252     "fig, ax = plt.subplots(2, 2, figsize=(10, 8))\n",
    253     "for i, n in enumerate(ns):\n",
    254     "    for j, p in enumerate(ps):\n",
    255     "        G = nx.generators.random_graphs.binomial_graph(n, p)\n",
    256     "        attack = Attack(G)\n",
    257     "        avrg_y = np.zeros(len(attack.num_nodes_removed))\n",
    258     "        for _ in range(100):\n",
    259     "            x_r, y_r = attack.random()\n",
    260     "            avrg_y += np.array(y_r)\n",
    261     "    \n",
    262     "        marker = '.'\n",
    263     "        if j == 1:\n",
    264     "            marker='o'\n",
    265     "        ax[i][j].plot(x_r, avrg_y/100, marker=marker, label=f\"(n, p) = ({n}, {p})\")\n",
    266     "        ax[i][j].set_xlabel(\"Number of Nodes removed\")\n",
    267     "        ax[i][j].set_ylabel(\"Porportion of nodes in Core\")\n",
    268     "        ax[i][j].legend(loc=\"best\")\n",
    269     "fig.suptitle(\"Random Attack on Erdos-Renyi Network (n, p)\", fontsize=16)"
    270    ]
    271   }
    272  ],
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