{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YoctkWf6zKAU"
      },
      "source": [
        "# Link prediction challenge"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "T4M6FQWOloni"
      },
      "outputs": [],
      "source": [
        "# Graph-tool is not available in the standard colab environment so we must first install it...\n",
        "%%capture\n",
        "!echo \"deb http://downloads.skewed.de/apt bionic main\" >> /etc/apt/sources.list\n",
        "!apt-key adv --keyserver keyserver.ubuntu.com --recv-key 612DEFB798507F25\n",
        "!apt-get update\n",
        "!apt-get install python3-graph-tool python3-matplotlib python3-cairo\n",
        "#python3-cairo from Ubuntu's reposity is linked with a different python version; we need to improvise\n",
        "!apt purge python3-cairo\n",
        "!apt install libcairo2-dev pkg-config python3-dev\n",
        "!pip install --force-reinstall --target=$nb_path pycairo\n",
        "!pip install --target=$nb_path zstandard"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "gbgXdgIF1_5R"
      },
      "outputs": [],
      "source": [
        "# Install node2vec to create embeddings\n",
        "%%capture\n",
        "# update gensim\n",
        "!pip install -U gensim\n",
        "!pip install node2vec"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YqXEdTKojiHW",
        "outputId": "2271fb3e-78e1-4cd5-a37c-d3eaaf9b13e3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/lib/python3/dist-packages/graph_tool/draw/cairo_draw.py:1500: RuntimeWarning: Error importing Gtk module: cannot import name '_gi' from 'gi' (/usr/lib/python3/dist-packages/gi/__init__.py); GTK+ drawing will not work.\n",
            "  warnings.warn(msg, RuntimeWarning)\n"
          ]
        }
      ],
      "source": [
        "# networks\n",
        "import networkx as nx\n",
        "import graph_tool.all as gt\n",
        "from graph_tool import topology, inference, generation, stats, correlations\n",
        "\n",
        "# machine learning\n",
        "from sklearn.metrics import f1_score, accuracy_score, precision_score, recall_score, classification_report, roc_auc_score,plot_roc_curve\n",
        "from sklearn.preprocessing import LabelEncoder, StandardScaler\n",
        "from sklearn.model_selection import train_test_split, GridSearchCV\n",
        "from sklearn.linear_model import LogisticRegression, LogisticRegressionCV\n",
        "from sklearn.metrics import accuracy_score\n",
        "\n",
        "# embeddings\n",
        "from sklearn.manifold import SpectralEmbedding\n",
        "from sklearn.decomposition import PCA, TruncatedSVD, NMF\n",
        "\n",
        "# Some math\n",
        "import scipy.sparse as sp\n",
        "import numpy as np\n",
        "from numpy.linalg import inv\n",
        "\n",
        "# data wrangling\n",
        "import pandas as pd\n",
        "from itertools import permutations, combinations, product\n",
        "\n",
        "# viz\n",
        "import pylab as plt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uO8Al5BizaeJ"
      },
      "source": [
        "## 1. Read network\n",
        "We are going to use a protein-protein interaction network from S. cervisiae (the yeast that is used to make beer, bread and all sort of yummy things): http://interactome.dfci.harvard.edu/S_cerevisiae/download/YuSci2008.pdf\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DsGXx40WsroU",
        "outputId": "22e8c8cf-e185-4f55-e5e0-d682564c0a6c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-07-20 06:27:16--  https://github.com/jgarciab/NetworkScience/raw/main/Data/ppi_network_prediction.graphml\n",
            "Resolving github.com (github.com)... 140.82.112.4\n",
            "Connecting to github.com (github.com)|140.82.112.4|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://raw.githubusercontent.com/jgarciab/NetworkScience/main/Data/ppi_network_prediction.graphml [following]\n",
            "--2022-07-20 06:27:16--  https://raw.githubusercontent.com/jgarciab/NetworkScience/main/Data/ppi_network_prediction.graphml\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.109.133, 185.199.108.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 117387 (115K) [text/plain]\n",
            "Saving to: ‘pp.graphml’\n",
            "\n",
            "pp.graphml          100%[===================>] 114.64K  --.-KB/s    in 0.02s   \n",
            "\n",
            "2022-07-20 06:27:16 (5.63 MB/s) - ‘pp.graphml’ saved [117387/117387]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Read network\n",
        "!wget https://github.com/jgarciab/NetworkScience/raw/main/Data/ppi_network_prediction.graphml -O pp.graphml\n",
        "G = nx.read_graphml(\"pp.graphml\", node_type=int)\n",
        "g = gt.load_graph('pp.graphml')\n",
        "\n",
        "num_vertices = g.num_vertices()\n",
        "\n",
        "# Initialize dataframe with all node pairs (potential links)\n",
        "df_all_pairs = pd.DataFrame(permutations(G.nodes(), 2))\n",
        "\n",
        "# Merge with dataframe with actual links to create dummy variable (link / no link)\n",
        "df_pos = pd.DataFrame(G.edges())\n",
        "df_pos[\"link\"] = 1\n",
        "df_all_pairs = pd.merge(df_all_pairs, df_pos, how=\"outer\")\n",
        "df_all_pairs[\"link\"] = df_all_pairs[\"link\"].fillna(0) #the ones that were not present in df_pos represent absence of links\n",
        "\n",
        "# Read test dataset\n",
        "test = pd.read_csv(\"https://github.com/jgarciab/NetworkScience/raw/main/Data/ppi_network_prediction_test.csv\", sep=\"\\t\", index_col=0)\n",
        "test.columns = [0,1,\"label\"]\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XR0OGKDunuCo"
      },
      "source": [
        "### How does this network look like?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 668
        },
        "id": "Zl_Njo_xnsWh",
        "outputId": "5d93e68d-5071-43f2-cfad-a3128fb3bc81"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Image object>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "image/png": {
              "width": 600,
              "height": 596
            }
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Global clustering:  0.020462906192519927\n",
            "Degree assortativity:  -0.1704172005377207\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(10,10))\n",
        "gt.graph_draw(g)\n",
        "\n",
        "\n",
        "print(\"Global clustering: \", nx.transitivity(G))\n",
        "print(\"Degree assortativity: \", nx.assortativity.degree_assortativity_coefficient(G))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "KN_XnVEgpI3c"
      },
      "outputs": [],
      "source": [
        "def create_predictions(df_all_pairs, df_s, test):\n",
        "  \"\"\"\n",
        "  Train a LogisticRegression given the labels from df_all_pairs and the scores from df_s. \n",
        "  The model is evaluated in the test dataset\n",
        "\n",
        "  df_all_pairs: Columns 0,1,label (label = presence of a link in the training data (the graph))\n",
        "  df_s: Columns 0,1,...\n",
        "  test: Columns 0,1, link (link = presence of a link in the test data (the actual graph))\n",
        "  \"\"\"\n",
        "  # Use all columns except the first two as independent variables\n",
        "  col_emb = list(df_s.columns)[2:]\n",
        "\n",
        "  # Merge the lables to the scores to create a model\n",
        "  df = pd.merge(df_all_pairs, df_s, how=\"left\", validate=\"1:1\")\n",
        "\n",
        "  # Create model\n",
        "  model = LogisticRegressionCV(cv=3, max_iter=1000, class_weight=\"balanced\", n_jobs=-1, scoring=\"f1\")\n",
        "  model.fit(df[col_emb], df[\"link\"])\n",
        "  print(model.coef_, model.intercept_)\n",
        "  # Predict labels\n",
        "  df[\"pred\"] = model.predict(df[col_emb])\n",
        "  \n",
        "  # Merge the predictions with the test dataset to evaluate the prediction\n",
        "  df_test = pd.merge(test, df)\n",
        "  \n",
        "  #recall = ability of the classifier to find all the positive samples.\n",
        "  #precision = ability of the classifier not to label as positive a sample that is negative.\n",
        "  print(classification_report(df_test[\"label\"],df_test[\"pred\"]))\n",
        "\n",
        "  # Plot ROC curve\n",
        "  plot_roc_curve(model, df_test[col_emb], df_test[\"label\"]) \n",
        "  plt.grid(True)\n",
        "\n",
        "  # return predicted probabilities\n",
        "  return model.predict_proba(df[col_emb])[:,0]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NiAVu4rinQWY"
      },
      "source": [
        "## 2. Methods based on similarity\n",
        "\n",
        "The following methods calculate node similarity looking mostly at (variations of) common neighbors.\n",
        "\n",
        "In graph-tool, this is done with the function s_jaccard = gt.vertex_similarity(g, \"jaccard\"): https://graph-tool.skewed.de/static/doc/topology.html#graph_tool.topology.vertex_similarity"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "LYz0T4glMCVq"
      },
      "outputs": [],
      "source": [
        "# create edgelist dataframe (to be able to merge with the networkx data)\n",
        "edgelist = pd.DataFrame([vi for vi in product(range(g.num_vertices()), repeat=2)])\n",
        "\n",
        "# map graph-tool labels to graphml node labels\n",
        "gt_to_graphml_labels = dict((i, int(g.vp['_graphml_vertex_id'][i])) for i in range(g.num_vertices()))\n",
        "edgelist[0] = edgelist[0].map(gt_to_graphml_labels)\n",
        "edgelist[1] = edgelist[1].map(gt_to_graphml_labels)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "ZW28xEmfHIpu"
      },
      "outputs": [],
      "source": [
        "# Calculate jaccard similarity, convert to dataframe (cols 0 and 1 are the node ids)\n",
        "## calculate jaccard similarity and convert to an array\n",
        "s_jaccard = gt.vertex_similarity(g, \"jaccard\")\n",
        "jaccard = edgelist.copy()\n",
        "jaccard['score'] = np.array([s_jaccard[i] for i in range(num_vertices)]).reshape(-1)\n",
        "jaccard['score'] = jaccard['score'].fillna(0) #there are somehow missing values (self-loops, but not only)\n",
        "\n",
        "\n",
        "## You can change the \"jaccard\" argument to creat enew one\n",
        "gt.vertex_similarity?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "Ejk58kkcoSFr",
        "outputId": "e15b76ba-94a1-41ac-c40c-d232533fd458"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[2.70713047]] [-0.0299722]\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.52      0.96      0.67       148\n",
            "           1       0.74      0.11      0.20       148\n",
            "\n",
            "    accuracy                           0.54       296\n",
            "   macro avg       0.63      0.54      0.44       296\n",
            "weighted avg       0.63      0.54      0.44       296\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_roc_curve is deprecated; Function :func:`plot_roc_curve` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: :meth:`sklearn.metric.RocCurveDisplay.from_predictions` or :meth:`sklearn.metric.RocCurveDisplay.from_estimator`.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "# create predictions\n",
        "prob_jac = create_predictions(df_all_pairs, jaccard, test)\n",
        "# save the probabilities for later (stacking algorithms)\n",
        "df_all_pairs[\"jaccard\"] = prob_jac"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### You can try some methods from here as well\n",
        "https://networkx.org/documentation/stable/reference/algorithms/link_prediction.html\n",
        "\n",
        "For example maybe nodes link proportionally to their degree"
      ],
      "metadata": {
        "id": "WxHnieqeeRAj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate pref attachment\n",
        "pa = nx.preferential_attachment(G, permutations(G.nodes(), 2))\n",
        "df_pa = pd.DataFrame(list(pa))\n",
        "df_pa.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "C3GSqzcNeO7s",
        "outputId": "86689690-9e60-46da-a05b-a40b1d1222de"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   0    1    2\n",
              "0  0    1  666\n",
              "1  0    2  814\n",
              "2  0  439   74\n",
              "3  0    8  444\n",
              "4  0    9  296"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b558c6bf-d5fb-4139-a00b-1d9f4eef6ac9\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>439</td>\n",
              "      <td>74</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>296</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b558c6bf-d5fb-4139-a00b-1d9f4eef6ac9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b558c6bf-d5fb-4139-a00b-1d9f4eef6ac9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b558c6bf-d5fb-4139-a00b-1d9f4eef6ac9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# create predictions\n",
        "prob_jac = create_predictions(df_all_pairs, df_pa, test)\n",
        "# save the probabilities for later (stacking algorithms)\n",
        "df_all_pairs[\"pa\"] = prob_jac"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "xCDIgFzCeMy9",
        "outputId": "2069787b-8e98-4678-fd35-3537d11e2e19"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0.05630451]] [-0.98060371]\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.60      0.86      0.71       148\n",
            "           1       0.76      0.43      0.55       148\n",
            "\n",
            "    accuracy                           0.65       296\n",
            "   macro avg       0.68      0.65      0.63       296\n",
            "weighted avg       0.68      0.65      0.63       296\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_roc_curve is deprecated; Function :func:`plot_roc_curve` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: :meth:`sklearn.metric.RocCurveDisplay.from_predictions` or :meth:`sklearn.metric.RocCurveDisplay.from_estimator`.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEGCAYAAABo25JHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3deXwV1fn48c+TjQQICQQIEJYAgsommyKlQLBFUakrgrhbrFq19VvU1rYWFPv9qa21fm1xl4pLQVyLiEtVIogLa2RfIokS9jUkhOzP74+ZxEsIuZPl5ia5z/v1yiuznJl5zr3JnJlzZs4RVcUYY0zoCgt2AMYYY4LLCgJjjAlxVhAYY0yIs4LAGGNCnBUExhgT4iKCHUB1tW3bVpOTk2u07dGjR2nRokXdBtTAWZ5Dg+U5NNQmzytXrtyvqu0qW9foCoLk5GRWrFhRo21TU1NJSUmp24AaOMtzaLA8h4ba5FlEvjvZOqsaMsaYEGcFgTHGhDgrCIwxJsRZQWCMMSHOCgJjjAlxASsIRGSWiOwVkXUnWS8i8oSIpIvIGhEZHKhYjDHGnFwg7wheBMZVsf58oJf7czPwVABjMcYYcxIBKwhUdTFwsIokFwMvqeMrIF5EOgYqHmOMaaxUlf99bwPbc0oDsv9gvlCWBGz3mc9yl+2qmFBEbsa5ayAxMZHU1NQaHTA3N7fG2zZWlufQYHlu2tbuK+a5lQVc11sDkudG8Waxqj4LPAswdOhQrembdfYmYmiwPIeGUMrzrFnLaB97hFHJ4QHJczCfGtoBdPGZ7+wuM8YY49q6J4fFW/Zx3fBuRIRJQI4RzIJgPnCd+/TQ2UC2qp5QLWSMMaFs1tJMmkWEcdWwbgE7RsCqhkRkDpACtBWRLGA6EAmgqk8DC4ELgHQgD7gxULEYY0xjdPBoIW+tyuKywUm0aREVsOMErCBQ1cl+1itwe6COb4wxjd2cZd9TUFzKjSO6B/Q49maxMcY0QIXFpcz+IpORvdrSOzE2oMeygsAYYxqghWt3sTengCk/DuzdAHioGhKRzsCVwEigE3AMWAe8B7yvqoF5w8EYY0KUqvLC5xn0bNeCUb0qHVSsTlV5RyAi/wJmAYXAI8Bk4DbgY5zuIz4XkVGBDtIYY0LJ8sxDrN2Rzc9/3J2wAD0y6svfHcHfVLWyTuPWAW+JSBTQte7DMsaY0DXr8wzim0dy2aDO9XK8Ku8IfAsBEWkjIm0qrC9U1fRABWeMMaFm+8E8Ptqwm6vO6kpMVHi9HNNf1VBXEZkrIvuAr4FlbtfSc0UkuT4CNMaYUPKvpZmEiXDd8OR6O6a/p4ZeA94GOqhqL1U9BegIvAPMDXRwxhgTSnLyi5i3YjsXDuhIh7joejuuv4Kgraq+pqolZQtUtURV5wIJgQ3NGGNCy7wVWeQWFNfLI6O+/DUWrxSRJ4HZ/NBldBfgemB1IAMzxphQUlKqvPhFBmcmt2ZA5/h6Pba/guA6YArwAM5YAeCMG/Au8EIA4zLGmJDy3w172H7wGH84//R6P3aVBYGqFuIMIWnDSBpjTADN+jyDzq1jOLdvh3o/do27mBCR8XUZiDHGhKq1WdksyzzIDT9KJrweXiCrqDZ9DZ1ZZ1EYY0wIm7U0gxZR4Uw8s4v/xAFQ44JAVafXZSDGGBOK9hzJ591vdjLxzC60io4MSgy1qRoaW5eBGGNMKHr5y+8oUeWGHyUHLYbaVA3ZU0PGGFML+UUlvPr1d4w9PZFuCS2CFkeVTw2JyPyTrcJeKDPGmFp5e/UODuUV1fsLZBX5e49gJHANkFthuQBnBSQiY4wJAarKrM8z6NupFWd1b+N/gwDyVxB8BeSp6mcVV4jI5sCEZIwxTd/irfvZujeXxyaegUj9PzLqy98LZedXsc4GpDHGmBqa9XkG7WKbMX5Ap2CHYmMWG2NMfUvfm8NnW/Zx3dndiIoI/mk4+BEYY0yIeeHzTJpFhHHVsIYxwKMVBMYYU48OHS3krVVZXDooiYSWzYIdDmAFgTHG1Kt/L/ueguJSfh7kR0Z9eS4IROT+quaNMcZUrbC4lJe+zGRkr7b0TowNdjjlqnNHsNLPvDHGmCosXLuLPUcKGtTdAFSjIFDVd6uaN8YYc3KqygufZ9CzXQtG92oX7HCO46+LiX8AerL1qvrrOo/IGGOaoBXfHWLtjmz+fEk/woIw5kBV/L1ZvKJeojDGmCbuhSUZxDeP5PLBnYMdygn8vVk823deRJqral5gQzLGmKZl+8E8Ptqwm1tH9yQmKjzY4ZzAUxuBiAwXkQ3AJnf+DBF50sN240Rks4iki8i9lazvKiKLRGS1iKwRkQuqnQNjjGngXvwikzARrhueHOxQKuW1sfhx4DzgAICqfgNU2deQiIQDM4HzgT7AZBHpUyHZfcA8VR0EXAn4LVyMMaYxyckv4rXl27lwQEc6xEUHO5xKVeepoe0VFpX42eQsIF1Vt6lqITAXuLjiboFW7nQcsNNrPMYY0xi8viKL3ILioI85UBV/jcVltovIjwAVkUjgTmCjn22SAN/CIwsYViHN/cBHIvIroAXw08p2JCI3AzcDJCYmkpqa6jHs4+Xm5tZ428bK8hwaLM8NU6kqTy0+Rq/4MA6mp5GaXrv9BSzPqur3B2gLvArsAfYBrwAJfraZADzvM38t8M8KaaYCd7nTw4ENQFhV+x0yZIjW1KJFi2q8bWNleQ4NlueG6f21u7Tb7xbowjU762R/tckzsEJPcl71dEegqvuBq6tZxuwAuvjMd3aX+ZoCjHOP8aWIRLuFzt5qHssYYxqcWUszSIqPYWyfxGCHUiWvTw31EJF3RWSfiOwVkf+ISA8/my0HeolIdxGJwmkMrjgG8vfAT9xjnA5E49xxGGNMo7ZuRzbLMg5y44hkIsIbdv+eXqP7NzAP6Ah0Al4H5lS1gaoWA3cAH+K0J8xT1fUiMkNELnKT3QX8QkS+cfd3g3sLY4wxjdqszzNoERXOxDO7+E8cZF4bi5ur6ss+86+IyD3+NlLVhcDCCsum+UxvAEZ4jMEYYxqFvUfyeXfNTq4e1o1W0ZHBDscvf30NtXEn33dfCJuL88jnJCqc4I0xxjhe+vI7ikuVG0ckBzsUT/zdEazEOfGX9ZB0i886BX4fiKCMMaaxyi8q4dWvv2Ps6Yl0S2gR7HA88dfXUMN9A8IYYxqgt1fv4FBeUYMbc6AqXtsIEJF+OF1FlL8jraovBSIoY4xpjFSVWZ9n0LdTK4Z1b+N/gwbCU0EgItOBFJyCYCFO/0GfA1YQGGOMa8nW/Wzdm8vfrjgDkYY15kBVvD4+OgHnef/dqnojcAZO30DGGGNcL3yeQbvYZvzsjE7BDqVavBYEx1S1FCgWkVY4b/42/IdjjTGmnqTvzeGzLfu47uxuREU07BfIKvLaRrBCROKB53CeJMoFvgxYVMYY08jMWppJVEQYVw3rGuxQqs1rX0O3uZNPi8gHQCtVXRO4sIwxpvE4dLSQt1ZlcdmgJBJaNgt2ONXm74WywVWtU9VVdR+SMcY0Lv9e9j35RaWN6pFRX/7uCP5WxToFzqnDWIwxptEpLC7lpS8zGdmrLb0TY4MdTo34e6FsTH0FYowxjdHCtbvYc6SAhy8fEOxQaqxxNW0bY0wDoqrMWppBj3YtGN2rXbDDqTErCIwxpoZWfHeINVnZ/HxEd8LCGs8LZBVZQWCMMTU06/MM4mIiuXxw52CHUiteRygTEblGRKa5811F5KzAhmaMMQ3X9oN5fLh+N1cN60pMVHiww6kVr3cET+IMLj/Znc8BZgYkImOMaQRe/CKTMBGuH54c7FBqzeubxcNUdbCIrAZQ1UPuOMTGGBNycvKLeG35di4c0JEOcdH+N2jgvN4RFIlIOM67A4hIO6A0YFEZY0wDVVqqvLZ8O7kFxfx8RON8gawir3cETwBvA+1F5H9xeiO9L2BRGWNMLRWVlJJXWMKxwhKOFhY7vwuKySsqIa+ghLzCYvIKS9yf4uN+Hy0o4VhRsfO7sIS8omJ3mxKOFZUAMKRba87oEh/kXNYNr30NvSoiK3G6ohbgElXdGNDIjDFNnqpSUFxa4WRcQl6BO13kM13hxJ2Zlc9Lmcs5WlDMsSLnJO+c9J2Td2GJ90oLEWgeGU7zZhE0jwqneZTzOzY6gsRWzWgRFUFMVDgtmkUQExlO86hwzu3bIYCfTP3yOjDNE8BcVbUGYmMM4JzED+UVsfPwMXYcPsb+3ALyCn64+s7zvRIvLOFYoXuFfdxJu5hS9X7MiDChuXtC1uJS2obn0zwqgjYtoujSurlzso4KJyYqwv3tpPU9uVecbtEsgmYRYY1qIJm65rVqaCVwn4icilNFNFdVVwQuLGNMsB0rLGFn9jF2Hj7GrsP57DjsTmfnl5/8C4orv+puFhFWfvXcotkPJ+ZO8ZHHn6TLrrTLTs7NKp6ond9l6Xz7+U9NTSUlZWR9fRxNmteqodnAbBFpA1wOPCIiXVW1V0CjM8YEREmpsjfHOaHvPFz2+xg7s3+YPpRXdNw2ItA+thmd4mM4vWMrfnJ6ezrFx9AxLoak+Bjat2pWfvIOb8Rv2YYiz4PXu04BTgO6AdZGYEwDpKocOVZcfjVf8QS/83A+u4/kU1KhTiY2OoJOcTF0io9mYJd4OsU7086yGBJbRTe6kbeMN17bCP4CXAp8C7wGPKiqhwMZmDGmcgXFJezOLquqyWfX4WOs2FjArG3L2OWe7I8Wlhy3TWS40CHOOakP696GjvHR7ok+hk5xMXSMj6ZVdGSQcmSCzesdwbfAcFXdH8hgjAl1paXK/qMF5Sf48pO9e3W/43A++3MLTtiuVRQkty+kR7sW/LhXW5LcKptO8dEkxcfQtmWzRt0pmgksfyOUnaaqm4DlQFcROW4wThuhzJjqyS0oPq6Kxqm28amyyc4/4bHHmMhwp4rGrZv3PcF3io+hQ1w0Xy1dQkrKj4OUK9PY+bsjmArcTOUjldkIZcacxJ4j+azNymbtjmzW7zxC1qE8dh4+xpH84uPShQl0aOWc5Ad2iadjf/cE71bXJMXHEBcTGdKPNprA8zdC2c3u5Pmqmu+7TkQafwcbxtSBspP+mh3ZrNvhnPz35TjVN2ECPdq1JDmhOWd1b+M+ZfPD1Xz72GZEhFsDrAkur20EXwAVB7KvbNlxRGQc8H9AOPC8qj5cSZqJwP04dxjfqOpVHmMypt7tOZLPGvdKv7KTfs92LRl5Slv6JcUxoHMcfTq1onlUdR/OM6Z++Wsj6AAkATEiMginewmAVkBzP9uG43RVPRbIApaLyHxV3eCTphfwe2CE26Np+xrnxJg6pKrsOVLA2h1+Tvq92tI/KY7+SXbSN42Xv7/a84AbgM7AYz7Lc4A/+Nn2LCBdVbcBiMhc4GJgg0+aXwAzVfUQgKru9Ry5MXWkspP+mqzs8qdzwgROaW8nfdN0iar/jj5E5HJVfbNaOxaZAIxT1Zvc+WtxxjW4wyfNO8AWYARO9dH9qvpBJfu6GafRmsTExCFz586tTijlcnNzadmyZY22bawsz8dTVQ4XKJlHSsnMLiXD/X2k0Pk/EKBTSyG5VTjJrcJIjguja2wYzSIadmOtfc+hoTZ5HjNmzEpVHVrZOn9VQ9eo6itAsohMrbheVR+rZLPqiAB6ASk4dx2LRaR/xZfVVPVZ4FmAoUOHakpKSo0O5vRNUrNtG6tQzvNxV/pZh90r/iMnXOn/tJ9zlT+gcxynd2ycV/qh/D2HkkDl2d9ffAv3d02KoB1AF5/5zu4yX1nA16paBGSIyBacgmF5DY5nQljZSX9N1mEWbC1kdsaySk/6o3u3o39SK/o34pO+MXXN3+Ojz7i/H6jBvpcDvUSkO04BcCVQ8Ymgd3DGQf6XiLQFegPbanAsE0JUld3uI5tljbi+J30Beifm20nfGI+q09fQn4FjwAfAAOA3brVRpVS1WETuAD7Eqf+fparrRWQGsEJV57vrzhWRDUAJcI+qHqhVjkyTUvlJP5v9uYWAc6Xfq32sz0k/nv3paZz3k1FBjtyYxsPrJdK5qvpbEbkUyAQuAxYDJy0IAFR1IbCwwrJpPtOK8/byCe0PJjTtyj5WftIve0Gr4kk/5dT29E+Ko19SHH06tiImKvy4faRmNOyGXWMaGq8FQVm6C4HXVTXbXnk3damopJR7Xv+Gd9J2As5Jv3ei/5O+Mab2vBYEC0RkE07V0C9FpB2Q72cbYzwpLC7lV3NW8eH6Pdwyugfn9ulgJ31j6pHXEcruddsJslW1RESO4rwcZkyt5BeVcPurq/hk016m/6wPN47oHuyQjAk5XhuLI4FrgFFuldBnwNMBjMuEgPyiEm5+eSWLt+zjz5f045qzuwU7JGNCkteqoaeASOBJd/5ad9lNgQjKNB2qysGjhWQeOErG/jwy9x8l48BRMvc7P3lFJfzl8gFMPLOL/50ZYwLCa0Fwpqqe4TP/qYh8E4iATON06GjhcSf4jAPOST/zwFFyfPrgDw8TurSOoVtCC85MbsM5p7VnVO92QYzcGOO1ICgRkZ6q+i2AiPTAee7fNFEFxSWkbt5HftGJX3NxibL9UN5xJ/zsY0Xl68MEklrHkJzQgku7JpGc0ILubVuQ3LYFnVvHEGn97xvToHgtCO4BFonINpwXN7sBNwYsKhNUqspv31jDf9xHOSsjAp3iYkhu25zxAzo6J/oE52TfpU0MzSLsiR9jGgu/BYH7qGg2TrfSZeMFbFbVE0fQNk3CK199x3/SdnLHmFO4dHDSCevDROgYF010pJ3sjWkK/PU+ehPw/4Bvge7AzW7XEKYJyj5WxDurd/Dn9zYw5tR2TB3bm7Awe3HQmKbO3x3B/wB9VXWf2y7wKmAFQROiqnydcZB5y7fz3tpdFBSXckaXeP4+aaAVAsaECH8FQaGq7gNQ1W0i0qweYjL1YG9OPm+u3MG8FdvJ2H+U2GYRTBjSmSvP7Eq/pFZYFyLGhA5/BUFnEXniZPOq+uvAhGUCobiklMVb9zF32XY+2bSXklLlrOQ23DHmFC7o39G6dDAmRPkrCO6pML8yUIGYuqeq7Dlayjurd7D6+0N8sH43e44U0LZlFDeN7M7EoV3o2S60hvozxpzI38A0s+srEFM3Nu46wn837GH194dI236YQ3lFQBrNo8IZ3iOBBy7qwk9Ob2/P8htjyvl7aug54P9UdV0l61oAk4ACVX01QPGZarr91VVkHDhKr/YtGdsnkebH9jLpp8Po1b4lEXbyN8ZUwl/V0Exgmoj0B9YB+4BonHGFWwGzcJ4kMkFUVFLKV9sO8P663WQdOsaEwZ356xVOjyCpqamc3rFVkCM0xjRk/qqG0oCJItISGAp0xBmTYKOqbq6H+MxJFBSX8PnW/by/bjcfb9zD4bwimkeFM7ZvonXlbIypFq/jEeQCqYENxfhzrLCE1M17eX/dbj7dtJfcgmJioyP46emJjOvXgdG929nbvsaYavPa15AJkpz8Ij7dtJf31+4mdcte8otKad08kgv7d2Rc/w6M6NmWqAir+zfG1JwVBA3YjsPHGPvYZ+QVltAuthkThnTm/H4dGda9jTX8GmPqTLUKAhFprqp5gQrG/KCs35+8whIeuKgv15zdjXDr8sEYEwBeh6r8EfA80BLoKiJnALeo6m2BDC7UFJeU8taqHby3dhdffLufohKlU1w055zW3goBY0zAeL0j+DtwHm6Hc6r6jYiMClhUISp18z5+++YaurSJ4cYR3RnXrwMDO8db52/GmIDyXDWkqtsrdERmI5TVscKSUgCev+5MTu0QG+RojDGhwmtBsN2tHlIRiQTuBDYGLixjjDH1xeujJ7cCtwNJwA5gIGDtA8YY0wR4vSM4VVWv9l0gIiOApXUfkjHGmPrktSD4BzDYwzJThcc/3sKTqd+iqpWuL3UXW9uwMaY++et9dDjwI6CdiEz1WdUKsL4MquGDdbt4/OOtjDm1XZWdwMU3j7QxAowx9crfHUEUzrsDEYDvYyxHgAmBCqqp2bYvl3teX8MZneN4+tohNIuwMtQY03D46330M+AzEXlRVb+r7s5FZBzwfzh3D8+r6sMnSXc58AZwpqquqO5xGipV5bXl2/nfhRsJDxdmXj3YCgFjTIPjtY0gT0T+CvTFGY8AAFU952QbiEg4zngGY4EsYLmIzFfVDRXSxeI8jvp1NWNv8J74JJ2/f7yFYd3b8MjlA+jcunmwQzLGmBN4fXz0VWAT0B14AMgElvvZ5iwgXVW3qWohMBe4uJJ0DwKPAPkeY2k0tuzJoVtCc+b84myS27YIdjjGGFMpr3cECar6gojc6VNd5K8gSAK2+8xnAcN8E4jIYKCLqr4nIvecbEcicjNwM0BiYiKpqakewz5ebm5ujbetib378inKL2Xx4s/q7ZgV1XeeGwLLc2iwPNcdrwVBkft7l4hcCOwE2tTmwCISBjwG3OAvrao+CzwLMHToUE1JSanRMVNTU6nptjXx+o5VHCrNISVldL0ds6L6znNDYHkODZbnuuO1IPiziMQBd+G8P9AK+B8/2+wAuvjMd3aXlYkF+gGpbh9GHYD5InJRU2owNsaYhs7rUJUL3MlsYAyUv1lcleVALxHpjlMAXAlc5bPPbKBt2byIpAJ3WyFgjDH1q8rGYhEJF5HJInK3iPRzl40XkS+Af1a1raoWA3cAH+J0UDdPVdeLyAwRuaiO4jfGGFNL/u4IXsCp3lkGPCEiO4GhwL2q+o6/navqQmBhhWXTTpI2xUvAxhhj6pa/gmAoMEBVS0UkGtgN9FTVA4EPzRhjTH3wVxAUqmopgKrmi8g2KwSqlpNfRPreXLbuzWXr3pxgh2OMMX75KwhOE5E17rQAPd15AVRVBwQ0ugbu+wN5LEnfx9Y9uaTvdX52H/nhvbio8DAmndmlij0YY0zw+SsITq+XKBqhw3mFjP/HEo7kF9M8KpxT2rfkRz0TOCWxJb3ax3JK+5Z0aR1DRLjXl7eNMSY4/HU6V+2O5kLFc0u2kVNQzBu3Dmdw19Y2wLwxptHyPHi9+cGB3AL+tTSTC/t3ZGhyrV6wNsaYoLN6ixp4+rNvyS8q4X9+2jvYoRhjTK15LghEJEZETg1kMI3FGyuzOL9/R05pbyOJGWMaP08FgYj8DEgDPnDnB4rI/EAG1tCUlCrLMg7ywLvryT5WRKe4aP8bGWNMI+C1jeB+nPEFUgFUNc3tQ6jJU1Uefn8Tb67awf7cAqIiwjjntEQmDLHHQo0xTYPnbqhVNdvtJbSMBiCeBudIfjHPLN7G4K7xTPtZH845rT0tm1kbuzGm6fB6RlsvIlcB4SLSC/g18EXgwmp4LhzQiYvO6BTsMIwxps55bSz+Fc54xQXAv3G6o/Y3HoExxphGwOsdwWmq+kfgj4EMxhhjTP3zekfwNxHZKCIPlo1LYIwxpmnwVBCo6hickcn2Ac+IyFoRuS+gkRljjKkXnl8oU9XdqvoEcCvOOwWVDjDT1BQUlQQ7BGOMCSivL5SdLiL3i8hanMHrv8AZjL7Je+Urp9+9s3tYn0LGmKbJa2PxLOA14DxV3RnAeBqUQ0cLmbU0kwv6d6Bvp7hgh2OMMQHhqSBQ1eGBDqQhembxNo4WFlvncsaYJq3KgkBE5qnqRLdKyPdN4iY/QlluQTGzv8jkojM60TsxNtjhGGNMwPi7I7jT/T0+0IE0NNnHijhWVMKPeiYEOxRjjAmoKhuLVXWXO3mbqn7n+wPcFvjwgk+wkceMMU2b18dHx1ay7Py6DMQYY0xw+Gsj+CXOlX8PEVnjsyoWWBrIwIwxxtQPf20E/wbeBx4C7vVZnqOqBwMWlTHGmHrjryBQVc0UkdsrrhCRNlYYGGNM4+fljmA8sBLn8VHfllMFegQoLmOMMfWkyoJAVce7v0NiWEpjjAlFXvsaGiEiLdzpa0TkMRHpGtjQjDHG1Aevj48+BeSJyBnAXcC3wMv+NhKRcSKyWUTSReTeStZPFZENIrJGRD4RkW7Vit4YY0yteS0IilVVgYuBf6rqTJxHSE9KRMKBmTjvG/QBJotInwrJVgND3a4q3gD+Up3gjTHG1J7XgiBHRH4PXAu8JyJhQKSfbc4C0lV1m6oWAnNxCpJyqrpIVfPc2a8Ika6tjTGmIfHaDfUk4Crg56q6220f+KufbZKA7T7zWcCwKtJPwXln4QQicjNwM0BiYiKpqakewz5ebm6up21LVVm91xmQZtPmTaQe/bZGx2sIvOa5KbE8hwbLc93x2g31bhF5FThTRMYDy1T1pboKQkSuAYYCo09y/GeBZwGGDh2qKSkpNTpOamoqVW375bcHeHfNTj5av5v9uYU0iwjjgh8PYWhy4x2Uxl+emyLLc2iwPNcdTwWBiEzEuQNIxXmX4B8ico+qvlHFZjuALj7znd1lFff9U+CPwGhVLfAYd53bsPMIk5/7iuZR4Yw5tT3j+nVgzGntadnM602TMcY0Tl7Pcn8EzlTVvQAi0g74GKeB92SWA71EpDtOAXAlTvVSOREZBDwDjCvbd7DkFRYD8NQ1Qxjdu10wQzHGmHrltbE4rMKJ+oC/bVW1GLgD+BDYCMxT1fUiMkNELnKT/RVoCbwuImkiMr964de9MOt12hgTYrzeEXwgIh8Cc9z5ScBCfxup6sKK6VR1ms/0Tz0eP2BUlU27c9i8JyfYoRhjTFB4bSy+R0QuA37sLnpWVd8OXFj1Z8V3h7ji6S/L55tHWZuAMSa0+BuPoBfwKNATWAvcraonNPg2Zrn5TtvAtPF9GNA5jsFd44MckTHG1C9/bQSzgAXA5Tg9kP4j4BEFyeBurRma3AYRayQwxoQWf/Ugsar6nDu9WURWBTqgQCstVTbsOkJhSSkA3+7LDXJExhgTXP4Kgmj3Ec+yy+QY33lVbXQFw4K1u/j1nNUnLG8eFR6EaIwxJvj8FQS7gMd85nf7zCtwTiCCCqSyNoHHJw0kvrnTXVJsdCS92rcMZljGGBM0/gamGVNfgdS34T0TSGwVHewwjDEm6Ly+UGaMMaaJsoLAGGNCnBUExhgT4ryOWSzuWMXT3PmuInJWYEMzxhhTH7zeETwJDAcmu/M5OMNQNholpcp3R0rIOpTnP7ExxtBJu4UAABlySURBVIQQrx3rDFPVwSKyGkBVD4lIVADjqnOvLd/O9C/ygW8RgWYRVitmjDHgvSAocgejVygfj6A0YFEFQE5+EQBPXj2YpPgY4ps3qnLMGGMCxmtB8ATwNtBeRP4XmADcF7CoAijl1HbWw6gxxvjw2g31qyKyEvgJTvcSl6jqxoBGZowxpl54HbO4K5AHvOu7TFW/D1Rgxhhj6ofXOpL3cNoHBIgGugObgb4BissYY0w98Vo11N93XkQGA7cFJCJjjDH1qkbPULrdTw+r41iMMcYEgdc2gqk+s2HAYGBnQCIyxhhTr7y2EcT6TBfjtBm8WffhmFBWVFREVlYW+fn5tdpPXFwcGzeG1kNtlufQ4CXP0dHRdO7cmcjISM/79VsQuC+Sxarq3Z73akwNZGVlERsbS3Jycq3Gjs7JySE2NtZ/wibE8hwa/OVZVTlw4ABZWVl0797d836rbCMQkQhVLQFGeN6jMTWUn59PQkJCrQoBY0KZiJCQkFDtu2p/dwTLcNoD0kRkPvA6cLRspaq+Vd1AjamKFQLG1E5N/oe8thFEAwdwxigue59AASsIjDGmkfP3+Gh794mhdcBa9/d69/e6AMdmTL1r2bJlrfexYsUKfv3rX590fWZmJv/+9789pwdITk6mf//+DBgwgNGjR/Pdd9/VOs668vTTT/PSSy/VePtly5YxatQoTj31VAYNGsRNN93Ehg0b6Ny5M6Wlx/dtOXDgQL7++usT9vHOO+8wY8aME9JeeeWVxy1LSUlhxYoV5fOZmZn069evyljy8mrXdX1GRgbDhg3jlFNOYdKkSRQWFp6QJjMzk5iYGAYOHMjAgQO59dZby9fNmTOn/Lu/9NJL2b9/PwB33303n376aa1iK6eqJ/0BdgHTgOmV/EyrattA/QwZMkRr4unUdO32uwV6tKCoRts3VosWLQp2CJ5t2LChTvZz5MiRGm/bokWLOomhKosWLdILL7ywWtt069ZN9+3bp6qq06ZN05tuuum49TXJc2lpqZaUlFR7u7q0e/du7dq1q37xxRfly15//XXdvXu3Dh8+XFNTU8uXb9y4UXv06FE+75vn4cOHl38+qs7fUr9+/bRTp06am5tbvnz06NG6fPny8vmMjAzt27ev31hq44orrtA5c+aoquott9yiTz755AlpfOPwVVRUpO3atSvP25133qnTp09XVdXMzEwdO3Zspces7H8JWKEnOa/6qxrapaoz/KQxps498O56Nuw8UqNtS0pKCA8PP2F5n06tmP6z6veKkpaWxq233kpeXh49e/Zk1qxZtG7dmuXLlzNlyhTCwsIYO3Ys77//PuvWrSM1NZVHH32UBQsW8Nlnn3HnnXcCTt3t4sWLuffee9m4cSMDBw7k+uuvZ9CgQeXpc3Nz+dWvfsWKFSsQEaZPn87ll19+XDzDhw/niSeeAGDfvn3ceuutZGRkEB4ezuOPP86IESPYt28fV111FTt37mT48OH897//ZeXKleTm5nLeeecxbNgwVq5cycKFC5k3bx7z5s2joKCASy+9lAceeICjR48yceJEsrKyKCkp4U9/+hOTJk3i3nvvZf78+URERHDuuefy6KOPcv/999OyZUvuvvvuk35WKSkpDBs2jEWLFnH48GFeeOEFRo4cycyZM7n++usZPnx4ef4mTJgAwOTJk5k7dy6jR48GYO7cuSdc4QNs2bKFZs2a0bZt2/Jlc+bM4dprr2Xjxo385z//4aqrrvL7PVcVS02pKp9++mn5HeD111/P/fffzy9/+UvP26sqR48eJSEhgZycHPr06QNAt27dOHDgALt376ZDhw61itNf1ZC13JmQd9111/HII4+wZs0a+vfvzwMPPADAjTfeyDPPPENaWlqlBQ/Ao48+ysyZM0lLS2PJkiXExMTw8MMPM3LkSNLS0vjNb35zXPoHH3yQuLg41q5dy5o1azjnnHNO2OcHH3zAJZdcAsCdd97Jb37zGz777DPefPNNbrrpJgAeeOABzjnnHNavX8+ECRP4/vsf+ofcunUrt912G+vXr2fz5s1s3bqVZcuWkZaWxsqVK1m8eDEffPABnTp14ptvvmHdunWMGzeOAwcO8Pbbb7N+/XrWrFnDffed2BP9yT4rgOLiYpYtW8bjjz9evnzdunUMGTKk0s9u4sSJvPPOOxQXFwPw2muvMXny5BPSLV26lMGDBx+37LXXXuPKK69k8uTJzJkzp9L9V1RVLL42b95cXoVT8efw4cPHpT1w4ADx8fFERDjX3J07d2bHjh2V7jcjI4NBgwYxevRolixZAkBkZCRPPfUU/fv3p1OnTmzatIkpU6aUbzN48GCWLl3qKX9V8XdH8JNaH8GYGqjJlXuZuny+PDs7m8OHD5dflV5//fVcccUVHD58mJycnPKrx6uuuooFCxacsP2IESOYOnUqV199NZdddhmdO3eu8ngff/wxc+fOLZ9v3bp1+fSYMWM4ePAgLVu25MEHHyxPv2HDBkpLSwkLC+PIkSPk5uby+eef8/bbbwMwbty44/bTrVs3zj77bAA++ugjPvroIwYNGgRAbm4uW7duZeTIkdx111387ne/Y/z48YwcOZLi4mKio6OZMmUK48ePZ/z48Z4+qzKXXXYZAEOGDCEzM7PKzwEgMTGRfv368cknn5CYmEhERMRx9flldu3aRbt27crnV6xYQdu2benatStJSUn8/Oc/5+DBg7Rp06bSJ2qq+5TNqaeeSlpaWrW28adjx458//33JCQksHLlSi655BLWr19PTEwMTz31FKtXr6ZHjx7ccsstPPTQQ+WFcPv27dm5s/adPFR5R6CqB2uzcxEZJyKbRSRdRO6tZH0zEXnNXf+1iCTX5njGNDT33nsvzz//PMeOHWPEiBFs2rSpxvtatGgR3333HQMHDmT69OkAlJaW8tVXX7F06VLS0tLYsWOH3wbvFi1alE+rKr///e9JS0sjLS2N9PR0pkyZQu/evVm1ahX9+/fnvvvuY8aMGURERLBs2TImTJjAggULGDduXLXib9asGQDh4eHlV/l9+/Zl5cqVJ92mrHpo7ty5ld4NAMTExBz33PycOXPYtGkTycnJ9OzZkyNHjvDmm05HCAkJCRw6dKg87cGDB8urlPzFUqY6dwQJCQkcPny4PL9ZWVkkJSVV+tkkJCQATkHZs2dPtmzZUl7g9OzZExHhsssu44svvijfLj8/n5iYGL8x+xOwgXvdN5JnAucDfYDJItKnQrIpwCFVPQX4O/BIoOIxpibi4uJo3bp1+a36yy+/zOjRo4mPjyc2Nrb8CRbfq3hf3377Lf379+d3v/sdZ555Jps2bSI2NpacnJxK048dO5aZM2eWz/uetAAiIiJ4/PHHeemllzh48CDnnnsu//jHP8rXl504RowYwbx58wDnqr/ifsqcd955zJo1i9zcXAB27NjB3r172blzJ82bN+eaa67hnnvuYdWqVeTm5pKdnc0FF1zA3//+d7755htPn1VV7rjjDmbPnn3ck0BvvfUWe/bsAZy7iIULF5ZX9VTm9NNPJz09HXAKxnnz5rF27VoyMzPJzMzkP//5T3n1UEpKCq+88krZwzDMnj2bMWPGeIqlTNkdQWU/8fHxx6UVEcaMGcMbb7xRfryLL774hDzs27ePkpISALZt28bWrVvp0aMHSUlJbNiwgX379gHw6aefcvrpp5dvt2XLlkrvkqorkGM2ngWkq+o2ABGZC1wMbPBJczFwvzv9BvBPEREt+5aMqWd5eXnHVd9MnTqV2bNnlzeA9ujRg3/9618AvPDCC/ziF78gLCyM0aNHExcXd8L+Hn/8cRYtWkRYWBh9+/bl/PPPJywsjPDwcM444wxuuOGG8moZgPvuu4/bb7+dfv36ER4ezvTp08urVMp07NiRyZMnM3PmTJ544gluv/12hg8fTmlpKaNGjeLpp59m+vTpTJ48mZdffpnhw4fToUMHYmNjy0/4Zc4991w2btxYXsXVsmVLXnnlFdLT07nnnnsICwsrr6fOycnh4osvJj8/H1XlscceOyG/J/usTiYxMZG5c+dy9913s3fvXsLCwhg1alT53UZ8fDzDhw9n9+7d9OjRo9J9jBo1irvuugtVZcmSJSQlJdGpU6fj1m/YsIFdu3Zx8803s2nTJs444wxEhKFDh/LQQw95iqWmHnnkEa688kruu+8+Bg0aVF7HP3/+fFasWMGMGTNYvHgx06ZNIzIykrCwMJ5++mnatGkDwPTp0xk1ahSRkZEkJSXxyiuvAE7fXOnp6QwdOrRW8QFIoM65IjIBGKeqN7nz1wLDVPUOnzTr3DRZ7vy3bpr9FfZ1M3AzQGJi4pCTXX1VZdWeYpZ8n88vB7cgKjx02sBzc3Pr5Nn4+hAXF8cpp5xS6/2c7Kmhuub72T722GPs3r2bv/zlLwE/bmUq5rmgoIDw8HAiIiL4+uuvmTp1ap00KjYkvnn+7W9/y/nnn19+dd9U+eb53XffJS0tjT/96U8npEtPTyc7O/u4ZWPGjFmpqpWWGo1iFHdVfRZ4FmDo0KGakpJS7X2kAINTU6nJto1ZaiPK88aNG+ukkbe+OiNbuHAhDz30EMXFxXTr1o0XX3wxaJ2gVczz7t27mThxIqWlpURFRfHCCy80uQ7afPN8//338/XXXze5PFbkm+fIyEj+8Ic/VJrn6Ojo4+40/QlkQbAD6OIz39ldVlmaLBGJAOJwurIwpsGbNGkSkyZNCnYYlerVqxerV68Odhj1JjExkYsuuijYYdQr3yeyaitgjcXAcqCXiHQXkSjgSmB+hTTzgevd6QnAp9Y+ENrs6zemdmryPxSwgkBVi4E7gA+BjcA8VV0vIjNEpKzofgFIEJF0YCpwwiOmJnRER0dz4MABKwyMqSF1xyOIjo6u1nYBbSNQ1YXAwgrLpvlM5wN1d39jGrXOnTuTlZVV/qhcTeXn51f7H6GxszyHBi95LhuhrDoaRWOxCQ2RkZHVGlXpZFJTU6vVUNYUWJ5DQ6DyHMg2AmOMMY2AFQTGGBPirCAwxpgQF7A3iwNFRPYBNR2eqS2w32+qpsXyHBosz6GhNnnupqrtKlvR6AqC2hCRFSd7xbqpsjyHBstzaAhUnq1qyBhjQpwVBMYYE+JCrSB4NtgBBIHlOTRYnkNDQPIcUm0ExhhjThRqdwTGGGMqsILAGGNCXJMsCERknIhsFpF0ETmhR1MRaSYir7nrvxaR5PqPsm55yPNUEdkgImtE5BMR6RaMOOuSvzz7pLtcRFREGv2jhl7yLCIT3e96vYj8u75jrGse/ra7isgiEVnt/n1fEIw464qIzBKRve4IjpWtFxF5wv081ojI4FofVFWb1A8QDnwL9ACigG+APhXS3AY87U5fCbwW7LjrIc9jgObu9C9DIc9uulhgMfAVMDTYcdfD99wLWA20dufbBzvuesjzs8Av3ek+QGaw465lnkcBg4F1J1l/AfA+IMDZwNe1PWZTvCM4C0hX1W2qWgjMBS6ukOZiYLY7/QbwExFpzAMZ+82zqi5S1Tx39iucEeMaMy/fM8CDwCNAfn0GFyBe8vwLYKaqHgJQ1b31HGNd85JnBVq503HAznqMr86p6mLgYBVJLgZeUsdXQLyIdKzNMZtiQZAEbPeZz3KXVZpGnQF0soGEeokuMLzk2dcUnCuKxsxvnt1b5i6q+l59BhZAXr7n3kBvEVkqIl+JyLh6iy4wvOT5fuAaEcnCGf/kV/UTWtBU9//dLxuPIMSIyDXAUGB0sGMJJBEJAx4DbghyKPUtAqd6KAXnrm+xiPRX1cNBjSqwJgMvqurfRGQ48LKI9FPV0mAH1lg0xTuCHUAXn/nO7rJK04hIBM7t5IF6iS4wvOQZEfkp8EfgIlUtqKfYAsVfnmOBfkCqiGTi1KXOb+QNxl6+5yxgvqoWqWoGsAWnYGisvOR5CjAPQFW/BKJxOmdrqjz9v1dHUywIlgO9RKS7iEThNAbPr5BmPnC9Oz0B+FTdVphGym+eRWQQ8AxOIdDY643BT55VNVtV26pqsqom47SLXKSqK4ITbp3w8rf9Ds7dACLSFqeqaFt9BlnHvOT5e+AnACJyOk5BULvxThu2+cB17tNDZwPZqrqrNjtsclVDqlosIncAH+I8cTBLVdeLyAxgharOB17AuX1Mx2mUuTJ4Edeexzz/FWgJvO62i3+vqhcFLeha8pjnJsVjnj8EzhWRDUAJcI+qNtq7XY95vgt4TkR+g9NwfENjvrATkTk4hXlbt91jOhAJoKpP47SDXACkA3nAjbU+ZiP+vIwxxtSBplg1ZIwxphqsIDDGmBBnBYExxoQ4KwiMMSbEWUFgjDEhzgqCJkhESkQkzecnuYq0uXVwvBdFJMM91ir37c7q7uN5EenjTv+hwrovahuju5+yz2WdiLwrIvF+0g+sSU+WItJRRBa40ykiku0ed6OITK/B/i4q63VTRC4p+5zc+Rnui4K14n6HE/ykSa3OC3lu3hd4SFdlb5tumkp73BSRdiLygdeYTOWsIGiajqnqQJ+fzHo45j2qOhC4F+fFtWpR1ZtUdYM7+4cK635UB/HBD59LP5z3R273k34gzvPa1TUVeM5nfon72QzF6ROnWt0Gq+p8VX3Ynb0Ep4fNsnXTVPXjGsTYkLwI+OsT6XycN6R7ATcDTwGo6j5gl4iMCGSATZ0VBCFARFqKMwbBKhFZKyIn9NLpXsUu9rliHukuP1dEvnS3fV1EWvo53GLgFHfbqe6+1onI/7jLWojIeyLyjbt8krs8VUSGisjDQIwbx6vuulz391wRudAn5hdFZIKIhIvIX0VkuXu1eIuHj+VL3I66ROQsN4+rReQLETnVfYt1BjDJjWWSG/ssEVnmpq2st1OAy4ETrlJV9SiwEjjFvdv4yo33bRFp7cbya/lh3Ii57rIbROSfIvIj4CLgr25MPX0+g3Ei8rrPZ1N+NV7d71BEprmf5ToReVbkuJ55r/X5GznLTe/1c6mUh942oeoeN98Brq7OMU0Fge5b237q/wfnjdI09+dtnDfIW7nr2uK8kVj2MmGu+/su4I/udDhOXz1tcU7sLdzlvwOmVXK8F4EJ7vQVwNfAEGAt0ALnjeb1wCCck+RzPtvGub9TcccLKIvJJ01ZjJcCs93pKJweGGNwrhDvc5c3A1YA3SuJM9cnf68D49z5VkCEO/1T4E13+gbgnz7b/z/gGnc6HqcfnxYVjtEdWOkznwIscKcTgEygL7AGGO0unwE87k7vBJqVHaNiHL6fte+8+x1/7/NdPQVcU8PvsI3P8peBn/l8R8+506Nw+8s/2edSIe9Dgeer+JtN5iT977vrFwA/9pn/xOfvJQlYG+z/u8b80+S6mDCAWwVSNiMikcD/E5FRQCnOP04isNtnm+XALDftO6qaJiKjcaohlroXhVE4V9KV+auI3IfTx8sUnL5f3lbnKhgReQsYiXOl/DcReQTnJLGkGvl6H/g/EWmGU5WwWFWPici5wACfOu44nCqEjArbx4hImpv/jcB/fdLPFpFeOF0URJ7k+OcCF4nI3e58NNDV3VeZjpzYz81IEVmN89k/jNMxXLyqfuaun41TMIFTQLwqIu/gXOl6ok5XDB8APxORN4ALgd/i9DLr9TssM0ZEfgs0B9rgFOLvuuvmuMdbLCKtxGlnOdnn4hvfCuAmr/mppr1ApwDtOyRYQRAargbaAUNUtUic3jijfRO4/9ijcE4gL4rIY8Ah4L+qOtnDMe5R1TfKZkTkJ5UlUtUtbh35BcCfReQTVZ3hJROqmi8iqcB5wCScQUrAGanpV6r6oZ9dHFPVgSLSHKfvmtuBJ3AGr1mkqpeK07CeepLtBbhcVTdXdQwqfLY4bQTjy3ciElfF9hfiXG3/DPijiPSvIm1Fc4E7cKpZVqhqjlut4/U7RESigSdxrra3i8j9HJ+fin3SKCf5XEQksRqx+1NVj5vROJ+7qSFrIwgNccBetxAYA5wwXrE4YxjvUdXngOdxhsr7ChghImV1/i1EpLfHYy4BLhGR5iLSAqdaZ4mIdALyVPUVnI7wKms4LXLvTCrzGk4nW2V3F+Cc1H9Zto2I9HaPWSl1Rmr7NXCX/NANedlJ5QafpDk4VWRlPgR+VVZnLk6PrhVtwanmOClVzQYOidsOA1wLfCbOGApdVHURThVOHE61mq+KMfn6DOfz/AU/FJLV/Q7LTvr73baEik8SlbXp/Bin18tsvH0utVVVj5u9gZM+cWT8s4IgNLwKDBWRtcB1wKZK0qQA37hVGJOA/1PniYwbgDkisganSuE0LwdU1VU49c7LcNoMnlfV1UB/YJlbRTMd+HMlmz8LrBG3sbiCj3CqOz5WZ+hCcAquDcAqcR5BfAY/d7tuLGtwBjX5C/CQm3ff7RYBfcoai3HuHCLd2Na78xX3exT4tuzEW4XrcarT1uA8nTQDp+3iFfd7Wg08oScOKDMXuMdtlO1Z4dglOHXp57u/qe536B7vOZwT64c4VYa+8t3P6WmcKkDw8LmI8yDA85UdU5zeNr8EThWRLBGZ4i6/VURudZMtxOlOO92N7zafXYwBmsoodEFhvY8aU8dE5FKcarj7gh1LKBCRxcDF6o7TbKrP2giMqWOq+raINOYxsBsNEWkHPGaFQO3YHYExxoQ4ayMwxpgQZwWBMcaEOCsIjDEmxFlBYIwxIc4KAmOMCXH/H0qcHAODUlxFAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7LKW4JYupYmv"
      },
      "source": [
        "## 3. Methods based on paths\n",
        "There are also methods that look not only at immediate neighbors, but also at longer-paths. You can do this using matrix multiplication (remember that A^2 represents the number of paths between i and j in two steps)\n",
        "\n",
        "\n",
        "One of this methods is Katz similarity."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ofYZ4bFFTXw0",
        "outputId": "b5c1b676-6218-4a1a-8fee-30c035d8e1d7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Largest eigenvalue: (2.000000000000016+0j)\n"
          ]
        }
      ],
      "source": [
        "## Katz index (https://stackoverflow.com/questions/62069781/how-to-find-the-similarity-between-pair-of-vertices-using-katz-index-in-python)\n",
        "\n",
        "#Calculate largest eigenvector\n",
        "L = L = gt.laplacian(g, norm=True)\n",
        "e = np.linalg.eigvals(L.A)\n",
        "print(\"Largest eigenvalue:\", max(e))\n",
        "beta = 1/max(e)\n",
        "I = np.identity(num_vertices) #create identity matrix\n",
        "\n",
        "#Katz score\n",
        "ks = inv(I - gt.adjacency(g)*beta) - I\n",
        "ks = np.array(ks.real)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "aphNDnIHU3pA"
      },
      "outputs": [],
      "source": [
        "# Put it into a nice format\n",
        "df_katz = edgelist.copy()\n",
        "df_katz[\"katz\"] = ks.reshape(-1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "JFx7inRFWQgA",
        "outputId": "a5bb0fe4-46ac-4c38-ad86-d513ff770a33"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[-0.21861468]] [-0.03336082]\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.50      0.84      0.63       148\n",
            "           1       0.52      0.17      0.26       148\n",
            "\n",
            "    accuracy                           0.51       296\n",
            "   macro avg       0.51      0.51      0.44       296\n",
            "weighted avg       0.51      0.51      0.44       296\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_roc_curve is deprecated; Function :func:`plot_roc_curve` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: :meth:`sklearn.metric.RocCurveDisplay.from_predictions` or :meth:`sklearn.metric.RocCurveDisplay.from_estimator`.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "# create predictions\n",
        "prob_jac = create_predictions(df_all_pairs, df_katz, test)\n",
        "# save the probabilities for later (stacking algorithms)\n",
        "df_all_pairs[\"katz\"] = prob_jac"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UdiO3IcH3HHZ"
      },
      "source": [
        "# 4. Methods based on SBM\n",
        "A SBM encodes the probability of two nodes in communities i and j linking to each other (with some corrections, e.g. hierarchies and degree-corrections). We can use those probabilities for link prediciton."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VuieCJ-Rcn9s",
        "outputId": "a827df91-3102-4bff-e926-c91089628f95"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "929296"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ],
      "source": [
        "#state = gt.minimize_nested_blockmodel_dl(g)\n",
        "\n",
        "#It takes too long to run (1+ hours) so I run it for you (this is not exactly how it should be done)\n",
        "#for an example on how to do it see here: https://graph-tool.skewed.de/static/doc/demos/inference/inference.html#edge-prediction-as-binary-classification\n",
        "#probs = [state.get_edges_prob([i], entropy_args=dict(partition_dl=False)) for i in list(product(range(g.num_vertices()), repeat=2))]\n",
        "probs = pd.read_csv(\"https://github.com/jgarciab/NetworkScience/raw/main/Data/ppi_sbm_probs.txt\", header=None).values\n",
        "len(probs)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "OFTfOlUgdJnF",
        "outputId": "3cf7553c-11e9-4ec2-85bf-d6ed5506d3b7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0.42249721]] [3.56583915]\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.67      0.30      0.41       148\n",
            "           1       0.55      0.85      0.67       148\n",
            "\n",
            "    accuracy                           0.57       296\n",
            "   macro avg       0.61      0.57      0.54       296\n",
            "weighted avg       0.61      0.57      0.54       296\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_roc_curve is deprecated; Function :func:`plot_roc_curve` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: :meth:`sklearn.metric.RocCurveDisplay.from_predictions` or :meth:`sklearn.metric.RocCurveDisplay.from_estimator`.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "# # Put it into a nice format\n",
        "df_sbm = edgelist.copy()\n",
        "df_sbm[\"sbm\"] = probs\n",
        "\n",
        "# create predictions\n",
        "prob_jac = create_predictions(df_all_pairs, df_sbm, test)\n",
        "# save the probabilities for later (stacking algorithms)\n",
        "df_all_pairs[\"sbm\"] = prob_jac"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hzgTXqcOlXM7"
      },
      "source": [
        "## 5. Methods based on node embeddings (spectral methods and matrix factorization; node2vec)\n",
        "The following methods will create node embeddings based on transformations of the adjacency matrix, and on random walks\n",
        "\n",
        "In order to predict a link, each pair of embeddings needs to be combined (e.g. by computing the L1 norm (np.abs(v1-v2))\n",
        "\n",
        "\n",
        "* 5.1 shows an example of a spectral method (you can try different methods: TruncatedSVD, PCA, SpectralEmbedding and NMF; you can modify the dimension of the embedding as well)\n",
        "* 5.2 shows an example of node2vec (you can change the p and q parameters, the length of walks, etc)\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "XmIMaaUkvqEL"
      },
      "outputs": [],
      "source": [
        "def calculate_dist(v1, v2):\n",
        "  \"\"\"\n",
        "  Calculate the L1 distance\n",
        "  \"\"\"\n",
        "  return np.abs(v1 - v2)\n",
        "\n",
        "def create_pair_distance(embeddings, G):\n",
        "  \"\"\"\n",
        "  Calculates the distance between embeddings using calculate_dist\n",
        "  \"\"\"\n",
        "  # Create dictionary with embeddings\n",
        "  df_clsvd = pd.DataFrame(embeddings)\n",
        "  df_clsvd.index = G.nodes()\n",
        "  df_clsvd = {k: row.values for k,row in df_clsvd.iterrows()}\n",
        "\n",
        "\n",
        "  # Calculate all distances and convert to dictionary\n",
        "  pairs = combinations(G.nodes(), 2)\n",
        "  all_pairs = [calculate_dist(df_clsvd[n1], df_clsvd[n2]) for n1,n2 in pairs]\n",
        "\n",
        "  # Concatenate labels with node pairs      \n",
        "  all_pairs = pd.DataFrame(all_pairs)\n",
        "  all_pairs =  pd.concat([pd.DataFrame(combinations(G.nodes(), 2)), all_pairs.reset_index(drop=True)], axis=1)\n",
        "  all_pairs.columns = [0,1]+[f\"_{i}\" for i in range(2, len(all_pairs.columns))]\n",
        "\n",
        "  # Add the reverse of the node pair\n",
        "  all_pairs = pd.concat([all_pairs, all_pairs.rename(columns={0:1, 1:0})])\n",
        "  \n",
        "  return all_pairs"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-RUAO1sK2IC8"
      },
      "source": [
        "### 5.1 Example with SVD\n",
        "Try also PCA, SpectralEmbedding and NMF \n",
        "\n",
        "Try different time of embeddings sizes (n_components)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "AjD9pwGFkALD"
      },
      "outputs": [],
      "source": [
        "A = nx.to_scipy_sparse_matrix(G)\n",
        "clusters_svd = TruncatedSVD(n_components=10)\n",
        "clusters_svd.fit(A)\n",
        "cl_svd = clusters_svd.components_.T\n",
        "\n",
        "# clusters_svd = SpectralEmbedding(affinity = 'precomputed', n_components=5)\n",
        "# clusters_svd.fit(A)\n",
        "# cl_svd = clusters_svd.embedding_"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "mX3CbAxnkKDr"
      },
      "outputs": [],
      "source": [
        "df_emb = create_pair_distance(cl_svd, G)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 538
        },
        "id": "kp2UXdfS0l_d",
        "outputId": "f3093742-7806-4f99-9450-828ea6b4c6f1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[-36.28328884  34.26897916 -53.2443673   48.44942599  29.14500109\n",
            "  -38.2030028   18.06738602 -19.05638867 -14.70890125  12.6913854 ]] [-0.52206639]\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.54      0.89      0.67       148\n",
            "           1       0.69      0.24      0.36       148\n",
            "\n",
            "    accuracy                           0.57       296\n",
            "   macro avg       0.62      0.57      0.52       296\n",
            "weighted avg       0.62      0.57      0.52       296\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_roc_curve is deprecated; Function :func:`plot_roc_curve` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: :meth:`sklearn.metric.RocCurveDisplay.from_predictions` or :meth:`sklearn.metric.RocCurveDisplay.from_estimator`.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "probs = create_predictions(df_all_pairs, df_emb, test)\n",
        "# save the probabilities for later (stacking algorithms)\n",
        "df_all_pairs[\"svd\"] = probs"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WPtiLF562OfM"
      },
      "source": [
        "## 5.2 Example with node2vec\n",
        "\n",
        "You can create and save more predictions by changing the q and p parameters"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "90eb36d222c74978b90a9b5cf63bd705",
            "ea850920ad7547b98d94f6b80c2fb907",
            "e5150c7271154e3aa3dbf8dd5615145c",
            "f0edfad5c0704aba90366149570e810e",
            "d3adde87e1504e9a83220b263620a750",
            "ef2b4725cd3e485e98829ac76a4fe43b",
            "568118a7df6c48158828b2dadc2473bb",
            "e02390b85ee5476891e3892fe53e114d",
            "09672b059554495890345105b0f3dc4b",
            "9ec276e7396244a6a4389ec95c23fc7a",
            "a5837fafd4fe48c2b4ca74a71543b4ef"
          ]
        },
        "id": "I4OUnOd5kKW0",
        "outputId": "121d3a32-dede-4a69-96cf-91f2c9bb9adb"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Computing transition probabilities:   0%|          | 0/964 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "90eb36d222c74978b90a9b5cf63bd705"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Generate walks\n",
        "from node2vec import Node2Vec\n",
        "dimensions = 32\n",
        "workers = 8\n",
        "node2vec = Node2Vec(G, dimensions=32, q=0.5, walk_length=30, num_walks=10, workers=8)  \n",
        "\n",
        "\n",
        "# Embed nodes (dimensions = embedding size)\n",
        "model = node2vec.fit(window=5, min_count=1, batch_words=4) \n",
        "#model = gensim.models.Word2Vec(vector_size = dimensions, workers=8, window=5, min_count=1, batch_words=4)\n",
        "\n",
        "#vocab = model.wv.index2word\n",
        "# Embeddings as a pandas dataframe\n",
        "node2vec = pd.DataFrame([model.wv.get_vector(str(_)) for _ in G.nodes()])\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "y3geyIBh4bkW"
      },
      "outputs": [],
      "source": [
        "# Create all distances\n",
        "df_emb = create_pair_distance(node2vec, G)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 648
        },
        "id": "9ehyDPSG7ntw",
        "outputId": "7f8aba2d-cf99-4c00-fdee-5211e9609ee9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/joblib/externals/loky/process_executor.py:705: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\n",
            "  \"timeout or by a memory leak.\", UserWarning\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[-0.83225408 -0.6535014  -0.97416743 -1.39524821 -0.98730006 -1.61758811\n",
            "  -1.0838009  -0.89281779 -1.02745361 -1.2272077  -0.43580854 -0.93986632\n",
            "  -1.17233603 -1.10995608 -0.97769812 -0.99228212 -0.93882219 -0.66714545\n",
            "  -0.04253248 -1.44931967 -1.37994548 -1.14858662 -1.13605278 -1.10056559\n",
            "  -0.79590351 -0.88724755 -0.53310068 -1.09963519 -0.99116285 -1.14964823\n",
            "  -0.44949794 -0.70041447]] [11.71743061]\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.54      0.96      0.69       148\n",
            "           1       0.81      0.17      0.28       148\n",
            "\n",
            "    accuracy                           0.56       296\n",
            "   macro avg       0.67      0.56      0.48       296\n",
            "weighted avg       0.67      0.56      0.48       296\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_roc_curve is deprecated; Function :func:`plot_roc_curve` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: :meth:`sklearn.metric.RocCurveDisplay.from_predictions` or :meth:`sklearn.metric.RocCurveDisplay.from_estimator`.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "# Caulate predictions\n",
        "probs = create_predictions(df_all_pairs, df_emb, test)\n",
        "# save the probabilities for later (stacking algorithms)\n",
        "df_all_pairs[\"node2vec\"] = probs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Vq3Uatu0uLbm"
      },
      "outputs": [],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jv4iI05t2PxZ"
      },
      "source": [
        "# 6. Stacking classifiers\n",
        "For each method we fitted a logisticregression, which returned a probability of two nodes being connected. \n",
        "\n",
        "We can now fit a meta-classifier, which takes those predictions and combines them in order to (hopefully) create a better classifier.\n",
        "\n",
        "You can try different algorithms apart from LogisticRegressionCV: https://scikit-learn.org/stable/supervised_learning.html#supervised-learning\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "vOYVq-_f2WCh",
        "outputId": "8f040f92-604a-4ade-9441-f40d89ca9a81"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     0    1  link   jaccard      katz       sbm       svd  node2vec        pa  \\\n",
              "0  213  214   0.0  0.507492  0.508339  0.415454  0.556214  0.943492  0.727228   \n",
              "1    2  470   0.0  0.507492  0.508339  0.415454  0.784493  0.944646  0.727228   \n",
              "2   81  233   0.0  0.507492  0.543861  0.415454  0.112142  0.838446  0.113062   \n",
              "3  138    0   0.0  0.507492  0.502438  0.415454  0.961769  0.469220  0.000000   \n",
              "4  510   94   0.0  0.507492  0.508339  0.415454  0.531688  0.692729  0.727228   \n",
              "\n",
              "   label  \n",
              "0      1  \n",
              "1      1  \n",
              "2      1  \n",
              "3      1  \n",
              "4      1  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c9544383-9749-4ef0-866c-348f4589f235\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>0</th>\n",
              "      <th>1</th>\n",
              "      <th>link</th>\n",
              "      <th>jaccard</th>\n",
              "      <th>katz</th>\n",
              "      <th>sbm</th>\n",
              "      <th>svd</th>\n",
              "      <th>node2vec</th>\n",
              "      <th>pa</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>213</td>\n",
              "      <td>214</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.507492</td>\n",
              "      <td>0.508339</td>\n",
              "      <td>0.415454</td>\n",
              "      <td>0.556214</td>\n",
              "      <td>0.943492</td>\n",
              "      <td>0.727228</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>470</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.507492</td>\n",
              "      <td>0.508339</td>\n",
              "      <td>0.415454</td>\n",
              "      <td>0.784493</td>\n",
              "      <td>0.944646</td>\n",
              "      <td>0.727228</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>81</td>\n",
              "      <td>233</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.507492</td>\n",
              "      <td>0.543861</td>\n",
              "      <td>0.415454</td>\n",
              "      <td>0.112142</td>\n",
              "      <td>0.838446</td>\n",
              "      <td>0.113062</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>138</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.507492</td>\n",
              "      <td>0.502438</td>\n",
              "      <td>0.415454</td>\n",
              "      <td>0.961769</td>\n",
              "      <td>0.469220</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>510</td>\n",
              "      <td>94</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.507492</td>\n",
              "      <td>0.508339</td>\n",
              "      <td>0.415454</td>\n",
              "      <td>0.531688</td>\n",
              "      <td>0.692729</td>\n",
              "      <td>0.727228</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c9544383-9749-4ef0-866c-348f4589f235')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c9544383-9749-4ef0-866c-348f4589f235 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c9544383-9749-4ef0-866c-348f4589f235');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ],
      "source": [
        "# Merge measures with labels\n",
        "df_test_stack = pd.merge(df_all_pairs, test, how=\"right\")\n",
        "df_test_stack.head()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 42,
      "metadata": {
        "id": "id9vYCRO2guX"
      },
      "outputs": [],
      "source": [
        "# Columns to use in the prediction\n",
        "col_pred = [\"jaccard\",\"katz\",\"svd\",\"node2vec\",\"sbm\",\"pa\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "poLlHrHLkANp",
        "outputId": "df127866-b7b5-4301-a01d-e83576cfff0f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[('jaccard', 16.080000047732558), ('katz', -3.9025388583673224), ('svd', -3.48960686383733), ('node2vec', -22.928492176202184), ('sbm', 16.92423346883417), ('pa', -15.48960963496193)] [2.41982852]\n",
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.53      0.99      0.69       148\n",
            "           1       0.91      0.14      0.24       148\n",
            "\n",
            "    accuracy                           0.56       296\n",
            "   macro avg       0.72      0.56      0.46       296\n",
            "weighted avg       0.72      0.56      0.46       296\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_roc_curve is deprecated; Function :func:`plot_roc_curve` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: :meth:`sklearn.metric.RocCurveDisplay.from_predictions` or :meth:`sklearn.metric.RocCurveDisplay.from_estimator`.\n",
            "  warnings.warn(msg, category=FutureWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "# Create model\n",
        "model = LogisticRegressionCV(cv=3, max_iter=1000, class_weight=\"balanced\", n_jobs=-1, scoring=\"f1\")\n",
        "model.fit(df_all_pairs[col_pred], df_all_pairs[\"link\"])\n",
        "# Print coefficients\n",
        "print(list(zip(col_pred, model.coef_[0])), model.intercept_)\n",
        "\n",
        "\n",
        "# Create predictions and evaluate model\n",
        "df_test_stack[\"pred\"] = model.predict(df_test_stack[col_pred])\n",
        "\n",
        "\n",
        "#recall = ability of the classifier to find all the positive samples.\n",
        "#precision = ability of the classifier not to label as positive a sample that is negative.\n",
        "print(classification_report(df_test_stack[\"label\"],df_test_stack[\"pred\"]))\n",
        "\n",
        "plot_roc_curve(model, df_test_stack[col_pred], df_test_stack[\"label\"]) \n",
        "plt.grid(True)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2R8q40HcsxqJ"
      },
      "outputs": [],
      "source": [
        "#Link prediction is hard!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "liwUCRYyhb_4"
      },
      "source": [
        "# 7. Explore some of the node pairs with the highest probability of a link\n",
        "You can look at our results and explore which proteins may be interacting \n",
        "\n",
        "e.g. using the test dataset (you can also find the ones with the highest probability of being a link in the full dataset)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_test_stack.loc[(df_test_stack[\"link\"]==0) & (df_test_stack[\"label\"]!=1) & (df_test_stack[\"pred\"]==1 ) ]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "et2MCFPYyd2T",
        "outputId": "a7bc5195-8a6d-4853-d76c-d412204a002c"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       0   1  link   jaccard      katz       sbm       svd  node2vec  \\\n",
              "182  856  97   0.0  0.507492  0.505667  0.415454  0.557029  0.110572   \n",
              "235  159  94   0.0  0.494223  0.498538  0.415454  0.526591  0.411523   \n",
              "\n",
              "           pa  label  pred  \n",
              "182  0.704328      0   1.0  \n",
              "235  0.000678      0   1.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-276e5ed2-ad13-416e-9213-fa5773c8d49a\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>0</th>\n",
              "      <th>1</th>\n",
              "      <th>link</th>\n",
              "      <th>jaccard</th>\n",
              "      <th>katz</th>\n",
              "      <th>sbm</th>\n",
              "      <th>svd</th>\n",
              "      <th>node2vec</th>\n",
              "      <th>pa</th>\n",
              "      <th>label</th>\n",
              "      <th>pred</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>182</th>\n",
              "      <td>856</td>\n",
              "      <td>97</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.507492</td>\n",
              "      <td>0.505667</td>\n",
              "      <td>0.415454</td>\n",
              "      <td>0.557029</td>\n",
              "      <td>0.110572</td>\n",
              "      <td>0.704328</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>235</th>\n",
              "      <td>159</td>\n",
              "      <td>94</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.494223</td>\n",
              "      <td>0.498538</td>\n",
              "      <td>0.415454</td>\n",
              "      <td>0.526591</td>\n",
              "      <td>0.411523</td>\n",
              "      <td>0.000678</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-276e5ed2-ad13-416e-9213-fa5773c8d49a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-276e5ed2-ad13-416e-9213-fa5773c8d49a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-276e5ed2-ad13-416e-9213-fa5773c8d49a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HR5nKzk5srty",
        "outputId": "bf2dfbd2-c062-4e34-96e5-1350cd3c412b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('YGL172W', 'YJL061W')"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ],
      "source": [
        "#\n",
        "d = nx.get_node_attributes(G, \"label\")\n",
        "d[856], d[97]\n",
        "\n",
        "#https://www.yeastgenome.org/locus/YGL172W\n",
        "#YGL172W: FG-nucleoporin component of central core of the nuclear pore complex; contributes directly to nucleocytoplasmic transport and maintenance of the nuclear pore complex (NPC) permeability barrier; found in stable complex with Nic96p and two other FG-nucleoproteins (Nsp1p and Nup57p) 2 \n",
        "#YJL061W: Linker nucleoporin component of the nuclear pore complex (NPC); also part of the NPC cytoplasmic filaments; contributes to nucleocytoplasmic transport and NPC biogenesis; forms stable associations with three FG-nucleoporins (Nsp1p, Nup159p, and Nup116p); relocalizes to the cytosol in response to hypoxia\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "236LZmOl94Ck"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "DdpjZRpw94Fw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "1eNYY-ns94If"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "tX4UxbIT94K3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zrH1cfoH24cn"
      },
      "source": [
        "# z. Example of Graph Neural Networks (graphSAGE )\n",
        "\n",
        "Sometimes we have metadata and can use it to improve our classification\n",
        "Tutorial: https://docs.dgl.ai/tutorials/blitz/4_link_predict.html#sphx-glr-tutorials-blitz-4-link-predict-py\n",
        "\n",
        "(note: there are also options to use GNNs without metadata)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 602
        },
        "id": "HGjDLHkAsrwa",
        "outputId": "0f637bb1-ab40-44f5-86c7-d3af04ca072c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Looking in links: https://data.dgl.ai/wheels/repo.html\n",
            "Collecting dgl-cu113\n",
            "  Downloading https://data.dgl.ai/wheels/dgl_cu113-0.9.0-cp37-cp37m-manylinux1_x86_64.whl (235.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 235.1 MB 38 kB/s \n",
            "\u001b[?25hRequirement already satisfied: networkx>=2.1 in /usr/local/lib/python3.7/dist-packages (from dgl-cu113) (2.6.3)\n",
            "Requirement already satisfied: numpy>=1.14.0 in /usr/local/lib/python3.7/dist-packages (from dgl-cu113) (1.21.6)\n",
            "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.7/dist-packages (from dgl-cu113) (2.23.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from dgl-cu113) (4.64.0)\n",
            "Requirement already satisfied: scipy>=1.1.0 in /usr/local/lib/python3.7/dist-packages (from dgl-cu113) (1.7.3)\n",
            "Collecting psutil>=5.8.0\n",
            "  Downloading psutil-5.9.1-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (281 kB)\n",
            "\u001b[K     |████████████████████████████████| 281 kB 14.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->dgl-cu113) (3.0.4)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->dgl-cu113) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->dgl-cu113) (2022.6.15)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->dgl-cu113) (2.10)\n",
            "Installing collected packages: psutil, dgl-cu113\n",
            "  Attempting uninstall: psutil\n",
            "    Found existing installation: psutil 5.4.8\n",
            "    Uninstalling psutil-5.4.8:\n",
            "      Successfully uninstalled psutil-5.4.8\n",
            "Successfully installed dgl-cu113-0.9.0 psutil-5.9.1\n"
          ]
        },
        {
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "psutil"
                ]
              }
            }
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: torch==1.12.0 in /usr/local/lib/python3.7/dist-packages (1.12.0+cu113)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch==1.12.0) (4.1.1)\n",
            "\u001b[31mERROR: Operation cancelled by user\u001b[0m\n"
          ]
        }
      ],
      "source": [
        "!pip install dgl-cu113 -f https://data.dgl.ai/wheels/repo.html\n",
        "!pip install torch==1.12.0\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vtyLy92NWI8x",
        "outputId": "ea7ce453-ef88-4896-a759-01766b26ad02"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "DGL backend not selected or invalid.  Assuming PyTorch for now.\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Setting the default backend to \"pytorch\". You can change it in the ~/.dgl/config.json file or export the DGLBACKEND environment variable.  Valid options are: pytorch, mxnet, tensorflow (all lowercase)\n"
          ]
        }
      ],
      "source": [
        "import dgl\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "import itertools\n",
        "import numpy as np\n",
        "import scipy.sparse as sp\n",
        "import pandas as pd\n",
        "import networkx as nx"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y6bGbuK5LY8l",
        "outputId": "983d507a-dd8f-4d5a-fd24-62f1e2d084b1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Downloading /root/.dgl/cora_v2.zip from https://data.dgl.ai/dataset/cora_v2.zip...\n",
            "Extracting file to /root/.dgl/cora_v2\n",
            "Finished data loading and preprocessing.\n",
            "  NumNodes: 2708\n",
            "  NumEdges: 10556\n",
            "  NumFeats: 1433\n",
            "  NumClasses: 7\n",
            "  NumTrainingSamples: 140\n",
            "  NumValidationSamples: 500\n",
            "  NumTestSamples: 1000\n",
            "Done saving data into cached files.\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "Graph(num_nodes=2708, num_edges=10556,\n",
              "      ndata_schemes={'train_mask': Scheme(shape=(), dtype=torch.bool), 'val_mask': Scheme(shape=(), dtype=torch.bool), 'test_mask': Scheme(shape=(), dtype=torch.bool), 'label': Scheme(shape=(), dtype=torch.int64), 'feat': Scheme(shape=(1433,), dtype=torch.float32)}\n",
              "      edata_schemes={})"
            ]
          },
          "execution_count": 29,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset = dgl.data.CoraGraphDataset()\n",
        "g = dataset[0]\n",
        "g"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ep02_EC_LckD"
      },
      "outputs": [],
      "source": [
        "# Split edge set for training and testing\n",
        "u, v = g.edges()\n",
        "\n",
        "eids = np.arange(g.number_of_edges())\n",
        "eids = np.random.permutation(eids)\n",
        "test_size = int(len(eids) * 0.1)\n",
        "train_size = g.number_of_edges() - test_size\n",
        "test_pos_u, test_pos_v = u[eids[:test_size]], v[eids[:test_size]]\n",
        "train_pos_u, train_pos_v = u[eids[test_size:]], v[eids[test_size:]]\n",
        "\n",
        "# Find all negative edges and split them for training and testing\n",
        "adj = sp.coo_matrix((np.ones(len(u)), (u.numpy(), v.numpy())))\n",
        "adj_neg = 1 - adj.todense() - np.eye(g.number_of_nodes())\n",
        "neg_u, neg_v = np.where(adj_neg != 0)\n",
        "\n",
        "neg_eids = np.random.choice(len(neg_u), g.number_of_edges())\n",
        "test_neg_u, test_neg_v = neg_u[neg_eids[:test_size]], neg_v[neg_eids[:test_size]]\n",
        "train_neg_u, train_neg_v = neg_u[neg_eids[test_size:]], neg_v[neg_eids[test_size:]]\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_g = dgl.remove_edges(g, eids[:test_size])"
      ],
      "metadata": {
        "id": "-i3t92BK6K57"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ZsNpbeYHM5Ai"
      },
      "outputs": [],
      "source": [
        "from dgl.nn import SAGEConv\n",
        "\n",
        "# ----------- 2. create model -------------- #\n",
        "# build a two-layer GraphSAGE model\n",
        "class GraphSAGE(nn.Module):\n",
        "    def __init__(self, in_feats, h_feats):\n",
        "        super(GraphSAGE, self).__init__()\n",
        "        self.conv1 = SAGEConv(in_feats, h_feats, 'mean')\n",
        "        self.conv2 = SAGEConv(h_feats, h_feats, 'mean')\n",
        "\n",
        "    def forward(self, g, in_feat):\n",
        "        h = self.conv1(g, in_feat)\n",
        "        h = F.relu(h)\n",
        "        h = self.conv2(g, h)\n",
        "        return h\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xt0SRPFFOG0W"
      },
      "outputs": [],
      "source": [
        "train_pos_g = dgl.graph((train_pos_u, train_pos_v), num_nodes=g.number_of_nodes())\n",
        "train_neg_g = dgl.graph((train_neg_u, train_neg_v), num_nodes=g.number_of_nodes())\n",
        "\n",
        "test_pos_g = dgl.graph((test_pos_u, test_pos_v), num_nodes=g.number_of_nodes())\n",
        "test_neg_g = dgl.graph((test_neg_u, test_neg_v), num_nodes=g.number_of_nodes())\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "MwjauvpmOMM5"
      },
      "outputs": [],
      "source": [
        "import dgl.function as fn\n",
        "\n",
        "class DotPredictor(nn.Module):\n",
        "    def forward(self, g, h):\n",
        "        with g.local_scope():\n",
        "            g.ndata['h'] = h\n",
        "            # Compute a new edge feature named 'score' by a dot-product between the\n",
        "            # source node feature 'h' and destination node feature 'h'.\n",
        "            g.apply_edges(fn.u_dot_v('h', 'h', 'score'))\n",
        "            # u_dot_v returns a 1-element vector for each edge so you need to squeeze it.\n",
        "            return g.edata['score'][:, 0]\n",
        "\n",
        "class MLPPredictor(nn.Module):\n",
        "    def __init__(self, h_feats):\n",
        "        super().__init__()\n",
        "        self.W1 = nn.Linear(h_feats * 2, h_feats)\n",
        "        self.W2 = nn.Linear(h_feats, 1)\n",
        "\n",
        "    def apply_edges(self, edges):\n",
        "        \"\"\"\n",
        "        Computes a scalar score for each edge of the given graph.\n",
        "\n",
        "        Parameters\n",
        "        ----------\n",
        "        edges :\n",
        "            Has three members ``src``, ``dst`` and ``data``, each of\n",
        "            which is a dictionary representing the features of the\n",
        "            source nodes, the destination nodes, and the edges\n",
        "            themselves.\n",
        "\n",
        "        Returns\n",
        "        -------\n",
        "        dict\n",
        "            A dictionary of new edge features.\n",
        "        \"\"\"\n",
        "        h = torch.cat([edges.src['h'], edges.dst['h']], 1)\n",
        "        return {'score': self.W2(F.relu(self.W1(h))).squeeze(1)}\n",
        "\n",
        "    def forward(self, g, h):\n",
        "        with g.local_scope():\n",
        "            g.ndata['h'] = h\n",
        "            g.apply_edges(self.apply_edges)\n",
        "            return g.edata['score']\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 46,
      "metadata": {
        "id": "7j2HpBolNqRW"
      },
      "outputs": [],
      "source": [
        "model = GraphSAGE(g.ndata['feat'].shape[1], 16)\n",
        "# You can replace DotPredictor with MLPPredictor.\n",
        "#pred = MLPPredictor(16)\n",
        "pred = DotPredictor()\n",
        "\n",
        "def compute_loss(pos_score, neg_score):\n",
        "    scores = torch.cat([pos_score, neg_score])\n",
        "    labels = torch.cat([torch.ones(pos_score.shape[0]), torch.zeros(neg_score.shape[0])])\n",
        "    return F.binary_cross_entropy_with_logits(scores, labels)\n",
        "\n",
        "def compute_auc(pos_score, neg_score):\n",
        "    scores = torch.cat([pos_score, neg_score]).numpy()\n",
        "    labels = torch.cat(\n",
        "        [torch.ones(pos_score.shape[0]), torch.zeros(neg_score.shape[0])]).numpy()\n",
        "    return roc_auc_score(labels, scores)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VcsJTME9N01E"
      },
      "outputs": [],
      "source": [
        "# ----------- 3. set up loss and optimizer -------------- #\n",
        "# in this case, loss will in training loop\n",
        "optimizer = torch.optim.Adam(itertools.chain(model.parameters(), pred.parameters()), lr=0.01)\n",
        "\n",
        "# ----------- 4. training -------------------------------- #\n",
        "all_logits = []\n",
        "for e in range(100):\n",
        "    # forward\n",
        "    h = model(train_g, train_g.ndata['feat'])\n",
        "    pos_score = pred(train_pos_g, h)\n",
        "    neg_score = pred(train_neg_g, h)\n",
        "    loss = compute_loss(pos_score, neg_score)\n",
        "\n",
        "    # backward\n",
        "    optimizer.zero_grad()\n",
        "    loss.backward()\n",
        "    optimizer.step()\n",
        "\n",
        "    if e % 5 == 0:\n",
        "        print('In epoch {}, loss: {}'.format(e, loss))\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "# ----------- 5. check results ------------------------ #\n",
        "from sklearn.metrics import roc_auc_score\n",
        "with torch.no_grad():\n",
        "    pos_score = pred(test_pos_g, h)\n",
        "    neg_score = pred(test_neg_g, h)\n",
        "    print('AUC', compute_auc(pos_score, neg_score))\n",
        "\n",
        "\n",
        "# Thumbnail credits: Link Prediction with Neo4j, Mark Needham\n",
        "# sphinx_gallery_thumbnail_path = '_static/blitz_4_link_predict.png'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wHr9erINN03q"
      },
      "outputs": [],
      "source": [
        "#embeddings\n",
        "h.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8haFmIMQFEih"
      },
      "outputs": [],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kSah4exCzNii"
      },
      "source": [
        "## This is how we created the network"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-hXaXBTrsrgl"
      },
      "outputs": [],
      "source": [
        "if 0:\n",
        "  # Create network for challenge\n",
        "  df = pd.read_csv(\"http://interactome.dfci.harvard.edu/S_cerevisiae/download/CCSB-Y2H.txt\",sep=\"\\t\",header=None)\n",
        "  df = pd.concat([df, df.rename(columns={0:1, 1:0})])\n",
        "\n",
        "  G = nx.from_pandas_edgelist(df, source=0, target=1)\n",
        "  G.remove_edges_from(nx.selfloop_edges(G))\n",
        "  Gcc = sorted(nx.connected_components(G), key=len, reverse=True)\n",
        "  G0 = G.subgraph(Gcc[0])\n",
        "\n",
        "  df = pd.DataFrame(G0.edges())\n",
        "  df = pd.concat([df, df.rename(columns={0:1, 1:0})]).drop_duplicates()\n",
        "\n",
        "  nodes = df[0].unique()\n",
        "  d_conv = dict(zip(nodes, range(len(nodes))))\n",
        "  df[0] = df[0].map(d_conv)\n",
        "  df[1] = df[1].map(d_conv)\n",
        "\n",
        "  G = nx.from_pandas_edgelist(df, source=0, target=1)\n",
        "\n",
        "  adj = nx.to_scipy_sparse_array(G, nodelist=range(len(G)))\n",
        "\n",
        "\n",
        "  u,v = np.nonzero(adj)\n",
        "  eids = np.arange(len(u))\n",
        "  eids = np.random.permutation(eids)\n",
        "  test_size = int(len(eids) * 0.1)\n",
        "  train_size = len(u) - test_size\n",
        "  test_pos_u, test_pos_v = u[eids[:test_size]], v[eids[:test_size]]\n",
        "  train_pos_u, train_pos_v = u[eids[test_size:]], v[eids[test_size:]]\n",
        "\n",
        "  # Find all negative edges and split them for training and testing\n",
        "  adj_neg =  adj.todense() + np.eye(len(G)) - 1\n",
        "  neg_u, neg_v = np.nonzero(adj_neg)\n",
        "\n",
        "  neg_eids = np.random.choice(len(neg_u), len(u))\n",
        "  test_neg_u, test_neg_v = neg_u[neg_eids[:test_size]], neg_v[neg_eids[:test_size]]\n",
        "  train_neg_u, train_neg_v = neg_u[neg_eids[test_size:]], neg_v[neg_eids[test_size:]]\n",
        "  # Positive and negative examples to test (50-50)\n",
        "  pos = pd.DataFrame(np.array([test_pos_u,test_pos_v]).T)\n",
        "  pos[\"label\"] = 1\n",
        "  neg = pd.DataFrame(np.array([test_neg_u,test_neg_v]).T)\n",
        "  neg[\"label\"] = 0\n",
        "  df = pd.concat([pos,neg])\n",
        "  df.to_csv(\"../Data/ppi_network_prediction_test.csv\", sep=\"\\t\")\n",
        "            \n",
        "  # Network with 10% removed\n",
        "  G.remove_edges_from(zip(test_pos_u, test_pos_v))\n",
        "  nx.set_node_attributes(G, {v:k for k,v in d_conv.items()}, name=\"label\")\n",
        "  nx.write_graphml(G, \"../Data/ppi_network_prediction.graphml\")\n",
        "\n",
        "\n",
        "x=  pd.merge(pd.DataFrame(G.edges()),df, how=\"outer\", indicator=True)\n",
        "x[\"_merge\"].value_counts()"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "day3b_link_prediction.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "90eb36d222c74978b90a9b5cf63bd705": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_ea850920ad7547b98d94f6b80c2fb907",
              "IPY_MODEL_e5150c7271154e3aa3dbf8dd5615145c",
              "IPY_MODEL_f0edfad5c0704aba90366149570e810e"
            ],
            "layout": "IPY_MODEL_d3adde87e1504e9a83220b263620a750"
          }
        },
        "ea850920ad7547b98d94f6b80c2fb907": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_ef2b4725cd3e485e98829ac76a4fe43b",
            "placeholder": "​",
            "style": "IPY_MODEL_568118a7df6c48158828b2dadc2473bb",
            "value": "Computing transition probabilities: 100%"
          }
        },
        "e5150c7271154e3aa3dbf8dd5615145c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_e02390b85ee5476891e3892fe53e114d",
            "max": 964,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_09672b059554495890345105b0f3dc4b",
            "value": 964
          }
        },
        "f0edfad5c0704aba90366149570e810e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_9ec276e7396244a6a4389ec95c23fc7a",
            "placeholder": "​",
            "style": "IPY_MODEL_a5837fafd4fe48c2b4ca74a71543b4ef",
            "value": " 964/964 [00:00&lt;00:00, 1242.45it/s]"
          }
        },
        "d3adde87e1504e9a83220b263620a750": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ef2b4725cd3e485e98829ac76a4fe43b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "568118a7df6c48158828b2dadc2473bb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "e02390b85ee5476891e3892fe53e114d": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "09672b059554495890345105b0f3dc4b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "9ec276e7396244a6a4389ec95c23fc7a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "a5837fafd4fe48c2b4ca74a71543b4ef": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        }
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}