To test the node2vec model of KarateClub on the LesMiserable graph (as reported in paper)

node2vec_karateclub_eval.ipynb

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   "source": [
    "\"\"\"\n",
    "Author: Mohit Mayank\n",
    "Idea: To test the node2vec model of KarateClub on the LesMiserable graph (as reported in paper)\n",
    "Tests: Run the test for two setting, \n",
    "    1. To test Homophily, run with p=1, q=0.5 and n_clusters=6\n",
    "    2. To test Structural equivalenc, run with p=1, q=2 and n_clusters=3\n",
    "Observation: Test 1 gives respectable result with community marked with same cluster. \n",
    "             Test 2 result not able to replicate as other parameters like walk_length and num_walks is not mentioned in paper.\n",
    "\n",
    "\n",
    "Node2Vec Paper: https://cs.stanford.edu/~jure/pubs/node2vec-kdd16.pdf\n",
    "\"\"\"\n",
    "# import\n",
    "import networkx as nx\n",
    "from karateclub import Node2Vec\n",
    "from sklearn.cluster import KMeans\n",
    "from pyvis.network import Network\n",
    "\n",
    "# functions\n",
    "def plot_graph(graph):\n",
    "    nt = Network(\"500px\", \"500px\", notebook=True)\n",
    "    nt.from_nx(graph)\n",
    "    return nt.show(\"nx.html\")\n",
    "\n",
    "# get data\n",
    "G = nx.generators.social.les_miserables_graph()\n",
    "# mapping for node label\n",
    "mapping = {}\n",
    "for i, node in enumerate(G.nodes()):\n",
    "    mapping[node] = i\n",
    "H = nx.relabel_nodes(G, mapping)\n",
    "# run node2vec \n",
    "model = Node2Vec(p=1, q=2)\n",
    "model.fit(H)\n",
    "# perform clustering\n",
    "kmeans = KMeans(n_clusters=3, random_state=0).fit(model.get_embedding())\n",
    "# color the nodes\n",
    "colors = [\"#46019b\", \"#007efe\", \"#00bb00\", \"#fef601\", \"#dd0000\", \"#232345\"]\n",
    "for i, x in enumerate(kmeans.labels_):\n",
    "    H.nodes[i]['color'] = colors[x]\n",
    "# plot the network\n",
    "plot_graph(H)"
   ]
  }
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