{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "49bf5cea-75a5-4aff-8ba0-3db46fb29f86",
   "metadata": {
    "tags": []
   },
   "source": [
    "# 1. Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7a2348d1-3e61-43f0-9aac-fcaf2a6c26ec",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx\n",
    "\n",
    "import graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b43142d4-eb58-4003-80b2-c4befe3e1598",
   "metadata": {},
   "source": [
    "Let's start by loading the datasets and by saving them into three separate dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0b0432d9-6d41-42b7-8451-dbd2ee9a390f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Answers to questions\n",
    "df_a2q = pd.read_table(\"data/sx-stackoverflow-a2q.txt\", \n",
    "                       delimiter=\" \", \n",
    "                       names=[\"src\", \"tgt\", \"timestamp\"],\n",
    "                       nrows=50000)\n",
    "\n",
    "# Comments to answers\n",
    "df_c2a = pd.read_table(\"data/sx-stackoverflow-c2a.txt\", \n",
    "                       delimiter=\" \", \n",
    "                       names=[\"src\", \"tgt\", \"timestamp\"],\n",
    "                       nrows=50000)\n",
    "\n",
    "# Comments to questions\n",
    "df_c2q = pd.read_table(\"data/sx-stackoverflow-c2q.txt\", \n",
    "                       delimiter=\" \", \n",
    "                       names=[\"src\", \"tgt\", \"timestamp\"],\n",
    "                       nrows=50000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae41bec1-64c6-43aa-8249-8e143736d99c",
   "metadata": {},
   "source": [
    "Let's also convert the UNIX times in the `timestamp` column into `datetime` objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b922c2bf-00af-4401-ba8b-e4b94a7cd0e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_a2q[\"timestamp\"] = pd.to_datetime(df_a2q[\"timestamp\"], unit='s')\n",
    "df_c2a[\"timestamp\"] = pd.to_datetime(df_c2a[\"timestamp\"], unit='s')\n",
    "df_c2q[\"timestamp\"] = pd.to_datetime(df_c2q[\"timestamp\"], unit='s')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bc107d8-6328-497c-be5d-cef2aef6c53a",
   "metadata": {},
   "source": [
    "Now we can save all three as separate graphs (ignoring rows with users commenting their own comments/answers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "9db44a45-ed4b-49e8-8fc4-d176e0b5f28e",
   "metadata": {},
   "outputs": [],
   "source": [
    "G_a2q = graph.graph_from_df(df_a2q)   \n",
    "G_c2a = graph.graph_from_df(df_c2a)\n",
    "G_c2q = graph.graph_from_df(df_c2q)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5f7ef5c-ec4c-45e6-a9c0-ffa6047cecc0",
   "metadata": {},
   "source": [
    "in order to merge them into a single graph $G$,  which will contain all nodes and edges in the three graphs, assigning to each edge a `timestamp` attribute (with the older date among the three graphs) and a `weight` attribute (i.e. $3$ if an edge is only in one graph, $2$ if it's in two, and $1$ if it's in all three)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "998bb598-ef3e-4ea2-9fad-e82b1bdf8ebc",
   "metadata": {},
   "outputs": [],
   "source": [
    "G = graph.merge_graphs(G_c2a, G_c2q)\n",
    "G = graph.merge_graphs(G, G_a2q)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb16ddef-2a65-48d3-b73f-86fd1814aac8",
   "metadata": {},
   "source": [
    "To check if our own implementation works, we can test it against `networkx`'s, and see if the two merged graphs have the same nodes and each of those has the same neighbors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "65cc9f21-0757-4f32-93d0-a4161fe34331",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK! Same nodes and neighbors\n"
     ]
    }
   ],
   "source": [
    "Gx_a2q = graph.graph_from_df(df_a2q, \"networkx\")   \n",
    "Gx_c2a = graph.graph_from_df(df_c2a, \"networkx\")\n",
    "Gx_c2q = graph.graph_from_df(df_c2q, \"networkx\")\n",
    "\n",
    "Gx = nx.compose(Gx_c2a, Gx_c2q)\n",
    "Gx = nx.compose(Gx, Gx_a2q)\n",
    "\n",
    "graph.test_graph(G, Gx)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f9bf5fb-12c7-4fff-9272-b73f02d7ff70",
   "metadata": {},
   "source": [
    "By merging the three graphs, we obtain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b7c1984c-32f1-46a9-bf21-f4cde5db890f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Directed graph with 17099 nodes and 104662 edges\n"
     ]
    }
   ],
   "source": [
    "G.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e62b7f76-0949-43fc-86f1-eb59379877af",
   "metadata": {},
   "source": [
    "where each edge has by default a direction (unlike $G_x$ which is undirected), which will be that of the older interaction between the two users (i.e. the first occurrence in the dataframe, whose entries are in chronological order from oldest to newest).\n",
    "\n",
    "For instance, let's take a look at a random subgraph of $G$ (some nodes won't appear to be connected to others but it's just because their neighbors won't be plotted: by design every node in the graph has at least a neighbor):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "4af6f61b-f7fc-41b4-9914-1516d16654b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt = graph.plot_subgraph(G)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cafa9f0-e3e7-45a5-8480-903b62d9d6f5",
   "metadata": {},
   "source": [
    "# 2/3. Functionalities & Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "072f3d80-5582-45ba-9220-6ddd2cc89b1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from func import func_selector\n",
    "import visual"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bc3db42-8960-4851-a5f7-2ce49c640d82",
   "metadata": {},
   "source": [
    "### Functionality 1 - Overall features of the graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe7bbcad-b6d0-4d03-af3a-4b14b7255bfa",
   "metadata": {},
   "source": [
    "Let's take a look at the overall features of one of the graphs we built and the distribution of the degrees of each of its nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b3aadde1-eb93-4a1d-b810-c975e48914c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Graph features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Directed</th>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Users</th>\n",
       "      <td>7864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Answers/comments</th>\n",
       "      <td>47196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Avg links per user</th>\n",
       "      <td>6.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dense (|E| ~ |V|^2)</th>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Graph features\n",
       "Directed                      True\n",
       "Users                         7864\n",
       "Answers/comments             47196\n",
       "Avg links per user            6.00\n",
       "Dense (|E| ~ |V|^2)          False"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/X7Gxsa7tDQ0NevTRRzV48GDNnj3bNcoWHBysF198Ubt27ZIkvfbaaxc9kgYAAHCl89pIWmRkpKZOnarU1FQ5HA6NGDFCvXr10vjx4zV58mQdOXJEX375pRoaGrR582ZJUs+ePfX0009ryZIlyszMVE1Njbp166aFCxd6q0wAAABTshitcL7uckx3rnq7WA8P7sF05yXw9TBza0M/PYdeehb99Bx66Vm+7qfPpjsBAADQcoQ0AAAAEyKkAQAAmBAhDQAAwIQIaQAAACZESAMAADAhQhoAAIAJEdIAAABMiJAGAABgQoQ0AAAAEyKkAQAAmBAhDQAAwIQIaQAAACZESAMAADAhQhoAAIAJEdIAAABMiJAGAABgQoQ0AAAAEyKkAQAAmBAhDQAAwIQIaQAAACZESAMAADAhQhoAAIAJEdIAAABMiJAGAABgQoQ0AAAAEyKkAQAAmBAhDQAAwIQIaQAAACZESAMAADAhQhoAAIAJEdIAAABMiJAGAABgQoQ0AAAAEyKkAQAAmBAhDQAAwIQIaQAAACZESAMAADAhQhoAAIAJEdIAAABMyKshLTc3VwkJCYqLi1N2dvZZ27ds2aLk5GQNHTpUEyZM0MmTJyVJhw4d0pgxYzRo0CA99thjqqqq8maZAAAApuO1kFZSUqKsrCy9/vrrysnJ0erVq/X111+7tldWViozM1MrV67Uxo0bdeONN2rZsmWSpCeffFKjR49WXl6eevbsqeXLl3urTAAAAFPyWkgrKChQdHS0OnbsqODgYMXHxysvL8+13eFwKCMjQ5GRkZKkG2+8UYcPH5bD4dD27dsVHx8vSUpJSWlyHAAAQFvgtZBWWloqu93uWo6IiFBJSYlruVOnTho4cKAkqaamRitXrtR9992n48ePKyQkRDabTZJkt9ubHAcAANAW2Lz1xk6nUxaLxbVsGEaT5dMqKio0ceJE3XTTTRo+fLhKSkrO2u9cxzUnLCykZUW7KTw8RP42q8LDvfs5bYHdHurrEloV+uk59NKz6Kfn0EvPMnM/vRbSunTpoh07driWy8rKFBER0WSf0tJSPfLII4qOjtasWbMkSZ07d1ZFRYUaGhpktVrPedyFHD1aKafTuPQvcQ52e6jKyyvlqG9QeXmlDMM7n9MW2O2hKiur8HUZrQb99Bx66Vn003PopWf5up9+fpZmB5a8Nt3Zr18/FRYW6tixY6qurlZ+fr5iY2Nd2xsaGvToo49q8ODBmj17tmu0zN/fX3379tWmTZskSTk5OU2OAwAAaAu8NpIWGRmpqVOnKjU1VQ6HQyNGjFCvXr00fvx4TZ48WUeOHNGXX36phoYGbd68WZLUs2dPPf3008rIyFB6erpWrFihrl27avHixd4qEwAAwJQsRiucr7sc052r3i7Ww4N7MN15CXw9zNza0E/PoZeeRT89h156lq/76bPpTgAAALScWyFt69atjBgBAABcRm6FtFdffVX33nuvli9frrKyMm/XBAAA0Oa5FdJWrVqlP//5zzp16pQeeOABPf744yosLPR2bQAAAG2W29ekXXPNNZo6darS09O1Z88eTZs2TUlJSSoqKvJmfQAAAG2SW7fg+P7777VmzRpt2LBBN954o2bNmqUBAwZo165dmjJlirZu3ertOgEAANoUt0LayJEjNXz4cL322mvq1q2ba32fPn10xx13eKs2AACANsut6c65c+fqiSeeaBLQcnJyJEnPPvusN+oCAABo05odSdu6davq6+u1dOlSBQUFuW7DUV9fr2XLlmnYsGGXo0YAAIA2p9mQVlxcrE8++URHjx7VK6+88q+DbDalpaV5uzYAAIA2q9mQNnHiRE2cOFHZ2dkaM2bM5aoJAACgzWs2pG3YsEHJycmqra3VqlWrztr+8MMPe60wAACAtqzZkPb9999Lkvbt23dZigEAAECjZkPa5MmTJUnPPPPMZSkGAAAAjZoNaUlJSc0enJub69FiAAAA0KjZkDZ37tzLVQcAAAB+otmQFhYWpuuuu05ffPHF5aoHAAAAukBIW7hwoV544QVNmjTprG0Wi0Xvvvuu1woDAABoy5oNaS+88IIk8QB1AACAy8ytB6yfOnVKK1as0LZt2+Tv76/Y2FiNHz9eAQEB3q4PAACgTXLrAetPPvmkjhw5ohkzZujxxx/Xvn37NH/+fG/XBgAA0Ga5NZL25ZdfNrndxp133qnk5GSvFQUAANDWuTWSdtVVV+nEiROu5VOnTik0NNRbNQEAALR5zY6knZ7StNlsSklJUVxcnPz8/LR161Z17979shQIAADQFjUb0jp27ChJ6tu3r/r27etan5iY6NWiAAAA2rpmQ9pvfvOb8247deqUx4sBAABAI7d+OLBlyxY999xzOnXqlAzDkNPp1IkTJ/T55597uz4AAIA2ya2QtnDhQk2ZMkV/+ctfNH78eG3ZskXt27f3dm0AAABtllu/7mzXrp0SEhLUu3dvBQYGKjMzU++//76XSwMAAGi73AppgYGBqqur0zXXXKPi4mL5+fnJYrF4uzYAAIA2y63pzp///Of61a9+pQULFujBBx/Uzp071alTJ2/XBgAA0Ga5FdIeffRRDR06VJGRkVq+fLm2b9/ObTgAAAC8yK2QJknffPONXn31VdlsNt19990KCwvzZl0AAABtmlvXpP3pT3/SM888o6CgIPn5+Wnu3LnKzs72dm0AAABtllsjaX/729+0Zs0ahYSESJLGjh2r0aNHa8yYMV4tDgAAoK1y+9edP70v2lVXXaXAwECvFQUAANDWNTuSlp+fL0n6t3/7N02YMEEjR46U1WpVTk6OevbseVkKBAAAaIuaDWmvvvpqk+VVq1a5Xh89etQ7FQEAAODiQlp9fb0Mw5C/v79XiwIAAGjr3Lom7ejRoxo3bpx69+6tXr16KTU1VSUlJd6uDQAAoM1yK6TNmzdPvXv3VkFBgQoKCtS3b19lZmZe8Ljc3FwlJCQoLi6u2Vt2zJw5U+vWrXMtr1+/XjExMUpOTlZycrKysrLcKRMAAKDVcOsWHPv379fSpUtdy5MnT9aQIUOaPaakpERZWVlat26dAgICNGrUKN15553q3r17k30yMjJUWFio6Oho1/o9e/YoPT2dpxoAAIA2y62RtPr6etXW1rqWq6urL/iA9YKCAkVHR6tjx44KDg5WfHy88vLymuyTm5ure++9V4MHD26yfvfu3Vq/fr2SkpI0ffp0nTx50t3vAwAA0Cq4FdISEhKUlpamN954Q2+++abGjh2r+Pj4Zo8pLS2V3W53LUdERJx1Hdu4ceM0cuTIs4612+2aMGGCNm7cqK5du2revHnulAkAANBquDXdOXHiRHXp0kUfffSRnE6nUlJSNGLEiGaPcTqdTUbbDMO44Ojbac8//7zr9bhx4zRw4EC3jjstLCzkova/WOHhIfK3WRUe7t3PaQvs9lBfl9Cq0E/PoZeeRT89h156lpn76VZI+8///E/9z//8j+6//36337hLly7asWOHa7msrEwREREXPK6iokJr165VWlqapMZwZ7Va3f5cSTp6tFJOp3FRx7jLbg9VeXmlHPUNKi+vlGF453PaArs9VGVlFb4uo9Wgn55DLz2LfnoOvfQsX/fTz8/S7MCSW9OdFRUVOnXq1EV9cL9+/VRYWKhjx46purpa+fn5io2NveBxwcHBevHFF7Vr1y5J0muvvXbRI2kAAABXOrdG0tq1a6cBAwboxhtvVHBwsGv9n/70p/MeExkZqalTpyo1NVUOh0MjRoxQr169NH78eE2ePFm33nrrOY+zWq1asmSJMjMzVVNTo27dumnhwoUX+bUAAACubBbjAvN1e/fu1ccff6za2lp16dKlybbhw4d7tbiWuhzTnaveLtbDg3sw3XkJfD3M3NrQT8+hl55FPz2HXnqWr/t5oenOZkfS1q5dqwULFujaa6/VDz/8oEWLFunuu+/2eJEAAABo6oLP7szNzVVkZKQ+//xzZWVlEdIAAAAugwv+cCAyMlKS1KdPHx0/ftzrBQEAAOACIe3M+5pd7K0wAAAA0DJu3YLjNHdvRgsAAIBL0+w1aV999ZVuv/1213JNTY1uv/1219MDPvvsM68XCAAA0BY1G9Leeeedy1UHAAAAfqLZkBYVFXW56gAAAMBPXNQ1aQAAALg8CGkAAAAmREgDAAAwIUIaAACACRHSAAAATIiQBgAAYEKENAAAABMipAEAAJgQIQ0AAMCECGkAAAAmREgDAAAwIUIaAACACRHSAAAATIiQBgAAYEKENAAAABMipAEAAJgQIQ0AAMCECGkAAAAmREgDAAAwIUIaAACACRHSAAAATIiQBgAAYEKENAAAABMipAEAAJgQIQ0AAMCECGkAAAAmREgDAAAwIUIaAACACRHSAAAATIiQBgAAYEKENAAAABMipAEAAJiQV0Nabm6uEhISFBcXp+zs7PPuN3PmTK1bt861fOjQIY0ZM0aDBg3SY489pqqqKm+WCQAAYDpeC2klJSXKysrS66+/rpycHK1evVpff/31Wfs8+uij2rx5c5P1Tz75pEaPHq28vDz17NlTy5cv91aZAAAApuS1kFZQUKDo6Gh17NhRwcHBio+PV15eXpN9cnNzde+992rw4MGudQ6HQ9u3b1d8fLwkKSUl5azjAAAAWjubt964tLRUdrvdtRwREaGioqIm+4wbN06StHPnTte648ePKyQkRDZbY2l2u10lJSXeKhMAAMCUvBbSnE6nLBaLa9kwjCbL53Ou/dw57qfCwkIuav+LFR4eIn+bVeHh3v2ctsBuD/V1Ca0K/fQceulZ9NNz6KVnmbmfXgtpXbp00Y4dO1zLZWVlioiIuOBxnTt3VkVFhRoaGmS1Wt0+7qeOHq2U02lcdM3usNtDVV5eKUd9g8rLK2UY3vmctsBuD1VZWYWvy2g16Kfn0EvPop+eQy89y9f99POzNDuw5LVr0vr166fCwkIdO3ZM1dXVys/PV2xs7AWP8/f3V9++fbVp0yZJUk5OjlvHAQAAtCZeC2mRkZGaOnWqUlNTNWzYMCUmJqpXr14aP368du/e3eyxGRkZWrNmjRISErRjxw5NmTLFW2UCAACYksVohfN1l2O6c9XbxXp4cA+mOy+Br4eZWxv66Tn00rPop+fQS8/ydT99Nt0JAACAliOkAQAAmBAhDQAAwIQIaQAAACZESAMAADAhQhoAAIAJEdIAAABMiJAGAABgQoQ0AAAAEyKkXQKLRbJYLL4uAwAAtEKEtBZqF2jTy28Va9WmYoIaAADwOJuvC7iSVdU4fF0CAABopRhJAwAAMCFCGgAAgAkR0gAAAEyIkAYAAGBChDQAAAATIqQBAACYECENAADAhAhpAAAAJkRIAwAAMCFCGgAAgAkR0gAAAEyIkAYAAGBChDQPsFgki8Xi6zIAAEArQki7RMFBNr38VrFWbSomqAEAAI+x+bqA1qCqxuHrEgAAQCvDSBoAAIAJEdIAAABMiJAGAABgQoQ0AAAAEyKkAQAAmBAhDQAAwIQIaQAAACZESAMAADAhQpqHWSwWnjwAAAAuGSHNg/z8pFWbeEQUAAC4dDwWykOCg2xa/9F3PCIKAAB4BCNpHlRdW+/rEgAAQCtBSAMAADAhr4a03NxcJSQkKC4uTtnZ2WdtLy4uVkpKiuLj4zV79mzV1zeORK1fv14xMTFKTk5WcnKysrKyvFkmAACA6XjtmrSSkhJlZWVp3bp1CggI0KhRo3TnnXeqe/furn1mzJih+fPnq3fv3po1a5bWrFmj0aNHa8+ePUpPT1diYqK3ygMAADA1r42kFRQUKDo6Wh07dlRwcLDi4+OVl5fn2n7w4EHV1NSod+/ekqSUlBTX9t27d2v9+vVKSkrS9OnTdfLkSW+VCQAAYEpeG0krLS2V3W53LUdERKioqOi82+12u0pKSlyvx44dq9tvv12LFy/WvHnz9Mc//tHtzw4LC/HANzi/8PAQ+dusP/kzmiyf3gcXZreH+rqEVoV+eg699Cz66Tn00rPM3E+vhTSn09nkXmGGYTRZbm77888/71o/btw4DRw48KI+++jRSjmdRktLb5bdHqry8ko56hv+/8/yk//1k6O+QZJUXl4pw/BODa2F3R6qsrIKX5fRatBPz6GXnkU/PYdeepav++nnZ2l2YMlr051dunRRWVmZa7msrEwRERHn3V5eXq6IiAhVVFToz3/+s2u9YRiyWq3eKhMAAMCUvBbS+vXrp8LCQh07dkzV1dXKz89XbGysa3tUVJQCAwO1c+dOSdKGDRsUGxur4OBgvfjii9q1a5ck6bXXXrvokTQAAIArndemOyMjIzV16lSlpqbK4XBoxIgR6tWrl8aPH6/Jkyfr1ltv1aJFizRnzhxVVlbqlltuUWpqqqxWq5YsWaLMzEzV1NSoW7duWrhwobfKBAAAMCWL0QovnLoc16T9des+lZ+oVnCQTadq6hUcZFNwkL/KT1RLkn6T0otr0i7A19cCtDb003PopWfRT8+hl57l63767Jo0AAAAtBwhDQAAwIQIaQAAACZESAMAADAhQhoAAIAJEdK8xGJRkycqAAAAXAxCmhcEB9n08lvFWrWpmKAGAABaxGs3s23rqmocvi4BAABcwRhJ8zIG0gAAQEsQ0rwoOMimv27dx5QnAAC4aIQ0LztVU+/rEgAAwBWIkAYAAGBChDQAAAATIqRdRhaLhevTAACAWwhpl4HFIvn5WbRqE/dOAwAA7uE+aV7WLrDxxrbtAm3cOw0AALiNkHYZVNU4ZMjwdRkAAOAKwnQnAACACRHSAAAATIiQBgAAYEKENAAAABMipPkAd+AAAAAXQki7zE4/dN3PjxvbAgCA8yOk+YBhSC+/xY1tAQDA+XGfNB/hxrYAAKA5jKQBAACYECNpPtY429k45WkYPJUAAAA0IqT5UHDQv57rafGTHhxwPUENAABIIqT53Onnep7rBwQWi4XQBgBAG8U1aSZlsVi0+r19/PoTAIA2ipBmQhaLRRaLdKqm3telAAAAH2G600QslsaAdvo6NQAA0HaRBEyiXeC/fkRwruvUTr/mGjUAANoGQpqJnA5nZ7JYLFq1qViS9HBCD4IaAABtACHN5E4Ppp1+QoHF0vhYqcbXjK4BANBa8cMBEzs9BfqXLfskNX04u59f4+ja6ed/nv4DAACtAyNpJnfmFOjph7OfvnZNkvz8pJf+1jgdOnZID9dIGyNsAABcuQhpV6CfBrfgIJvWf/SdqmocPMEAAIBWhJDWClTX/ut+aj/9Zejp54KeK6hxPRsAAObm1WvScnNzlZCQoLi4OGVnZ5+1vbi4WCkpKYqPj9fs2bNVX98YNg4dOqQxY8Zo0KBBeuyxx1RVVeXNMlul09ezrdpULD8/S5Pr1s68nk3SOa9r4xo3AAB8x2shraSkRFlZWXr99deVk5Oj1atX6+uvv26yz4wZM/T73/9emzdvlmEYWrNmjSTpySef1OjRo5WXl6eePXtq+fLl3iqzVTs9qvbyW8X667v7tGHbd1q1qfGHCFU1DlXVOGSxSH5+Fte206HOz6/xsVRnBrxz/Z3LmWHvzDAIAACa57XpzoKCAkVHR6tjx46SpPj4eOXl5ek3v/mNJOngwYOqqalR7969JUkpKSl67rnnNHLkSG3fvl3PP/+8a/0vf/lLzZgxw1ultnqua9gsZ1/P5nq6wf9vO3Pd6dfVtfVqF2hTuyCbjp2sca2Tmv5YQWq8Tchft+7TqJ9fL6nxPSTpkcQerh84PJzQ4//3PXdgOz0N+9PtZ07Nnm/bxU7lMvULADAjr4W00tJS2e1213JERISKiorOu91ut6ukpETHjx9XSEiIbDZbk/UXw8/PuyM1fn4W2Tu2k7/VT0EBNtXU1SsowKagQOsVt+5C+5+oqFVQgE3+Nj/Xuvp6Z5N1H+85opOVtQr0t6rW0aBAf6vCr2qntz75XoH+VnVoH6CgAJs+2n1EHdoHSJKs1sZ/o21fnH2sn8Wi+/r+TJKUW7C/ybp/3SNO+rDosE5W1kqSkvp1k2E0rs8t2N9kXXMudn+zs1q5q46n0EvPop+eQy89q7l+evv/vF8or3gtpDmdzrNGOn66fL7tZ+4nXfy1UZ06tW9h1e7p3Lm9Hoy7yauf0VYk9+/e7PbUIbdc9LHNHeOJ/c2sc2fvnvttCb30LPrpOfTSs8zcT6/F8S5duqisrMy1XFZWpoiIiPNuLy8vV0REhDp37qyKigo1NDSc8zgAAIC2wGshrV+/fiosLNSxY8dUXV2t/Px8xcbGurZHRUUpMDBQO3fulCRt2LBBsbGx8vf3V9++fbVp0yZJUk5OTpPjAAAA2gKL4cUJ19zcXL3wwgtyOBwaMWKExo8fr/Hjx2vy5Mm69dZb9b//+7+aM2eOKisrdcstt+iZZ55RQECADh48qPT0dB09elRdu3bV4sWLddVVV3mrTAAAANPxakgDAABAy/ATEQAAABMipAEAAJgQIQ0AAMCECGkAAAAmREgDAAAwIUKam3Jzc5WQkKC4uDhlZ2f7upwr0kMPPaQhQ4YoOTlZycnJ2rVrlwoKCpSUlKS4uDhlZWX5ukTTq6ysVGJiog4cOCBJ5+1fcXGxUlJSFB8fr9mzZ6u+vt5XJZvWmb184oknFBcX5zo/33nnHUn00h3/9V//pSFDhmjIkCFauHChJM7NljpXLzk3W27p0qVKSEjQkCFDtGrVKklX2Llp4IKOHDliDBgwwDh+/LhRVVVlJCUlGfv27fN1WVcUp9NpxMTEGA6Hw7Wuurra6N+/v/HDDz8YDofDGDt2rPH+++/7sEpz+8c//mEkJiYat9xyi/HPf/6z2f4NGTLE+Pzzzw3DMIwnnnjCyM7O9mHl5nNmLw3DMBITE42SkpKz9qWXzdu2bZvx4IMPGrW1tUZdXZ2Rmppq5Obmcm62wLl6mZ+fz7nZQp9++qkxatQow+FwGNXV1caAAQOM4uLiK+rcZCTNDQUFBYqOjlbHjh0VHBys+Ph45eXl+bqsK8q3334rSRo7dqyGDh2q1157TUVFRbr22mt19dVXy2azKSkpib42Y82aNcrIyHA9Ju18/Tt48KBqamrUu3dvSVJKSgp9PcOZvayurtahQ4c0a9YsJSUl6bnnnpPT6aSXbrDb7UpPT1dAQID8/f113XXXaf/+/ZybLXCuXh46dIhzs4XuuOMOvfLKK7LZbDp69KgaGhr0448/XlHnptcesN6alJaWym63u5YjIiJUVFTkw4quPD/++KPuuusuzZ07Vw6HQ6mpqRo3btxZfS0pKfFhleb29NNPN1k+13lZUlJy1nq73U5fz3BmL8vLyxUdHa2MjAyFhobq17/+td58801df/319PICrr/+etfr/fv36+2339Yvf/lLzs0WOFcvs7Oz9fe//51zs4X8/f313HPP6eWXX9agQYOuuP9uMpLmBqfTKYvF4lo2DKPJMi6sT58+WrhwoUJDQ9W5c2eNGDFCzz33HH29BOc7LzlfL97VV1+t559/XhEREWrXrp0eeughffDBB/TyIuzbt09jx47VzJkzdfXVV3NuXoKf9vLf//3fOTcv0eTJk1VYWKjDhw9r//79V9S5SUhzQ5cuXVRWVuZaLisrc02TwD07duxQYWGha9kwDEVFRdHXS3C+8/LM9eXl5fT1Ar766itt3rzZtWwYhmw2G710086dO5WWlqbf/va3Gj58OOfmJTizl5ybLffNN9+ouLhYktSuXTvFxcXp008/vaLOTUKaG/r166fCwkIdO3ZM1dXVys/PV2xsrK/LuqJUVFRo4cKFqq2tVWVlpdavX69p06bpu+++0/fff6+Ghgb97W9/o68X4bbbbjtn/6KiohQYGKidO3dKkjZs2EBfL8AwDP3hD3/QyZMn5XA4tHr1ag0cOJBeuuHw4cOaOHGiFi1apCFDhkji3Gypc/WSc7PlDhw4oDlz5qiurk51dXV69913NWrUqCvq3OSaNDdERkZq6tSpSk1NlcPh0IgRI9SrVy9fl3VFGTBggHbt2qVhw4bJ6XRq9OjR6tOnj5599llNmjRJtbW16t+/vwYNGuTrUq8YgYGB5+3fokWLNGfOHFVWVuqWW25Ramqqj6s1t5tuukm/+tWv9Itf/EL19fWKi4tTYmKiJHp5IS+99JJqa2v17LPPutaNGjWKc7MFztdLzs2W6d+/v4qKijRs2DBZrVbFxcVpyJAh6ty58xVzbloMwzB8XQQAAACaYroTAADAhAhpAAAAJkRIAwAAMCFCGgAAgAkR0gAAAEyIW3AAaLUOHDiggQMH6oYbbpDU+JSG9u3bKzU1VQkJCT6uDgCaR0gD0KoFBQVpw4YNruWDBw8qLS1NVqtV8fHxPqwMAJpHSAPQpkRFRWny5Ml66aWXNGDAAC1atEjbt29XQ0ODbr75Zs2ZM0chISEqKipSZmamHA6HrrnmGh06dEjp6emSGh/QHhwcrKqqKq1du1Yff/yxVqxYIYfDoaCgIP3ud79Tnz59JEkrVqxQfn6+nE6noqKilJGRocjISF+2AMAVgpAGoM256aabtHfvXq1cuVJWq1Xr1q2TxWLR4sWLXXcdnzRpkubNm6f+/fvrk08+UVpamuv4ffv2acuWLYqKitL+/fuVlZWlV155RZ06ddK+ffv08MMPKz8/X/n5+dq7d6/eeOMN2Ww2rV69WnPmzNF///d/++7LA7hiENIAtDkWi0VBQUF6//33VVFRoYKCAkmSw+FQWFiY9u7dK6nxsTKSFB0dreuvv951fNeuXRUVFSVJ2rZtm0pLS5uEOIvFoh9++EHvvfeedu/erfvvv19S4zVx1dXVl+MrAmgFCGkA2pzdu3frhhtuUGVlpWbNmuUKY1VVVaqtrVVZWZnOfGKe1Wp1vQ4ODna9djqduuuuu7RkyRLXusOHDysiIkJOp1Pjxo3T6NGjJUl1dXU6efKkF78ZgNaEW3AAaFO+++47LV++XGPHjlVMTIyys7NVV1cnp9OpuXPnavHixbruuusUEBCgDz/8UJJUVFSkvXv3ymKxnPV+d911l7Zt26ZvvvlGkvTBBx9o6NChqqmpUUxMjN58801VVlZKkpYuXaqZM2devi8L4IrGSBqAVq2mpkbJycmSJD8/PwUGBmratGm65557FB0drQULFmj48OFqaGhQjx49lJ6eLpvNpmXLlikjI0OLFy9Wt27dFB4erqCgoLOmK7t376558+Zp2rRpMgxDNptNK1asUPv27TVy5EiVlJTogQcekMViUdeuXfXss8/6og0ArkAW48wxfQCAFixYoEceeUTh4eE6fPiwkpOTtWXLFnXo0MHXpQFoIxhJA4BziIqKUlpammw2mwzD0Pz58wloAC4rRtIAAABMiB8OAAAAmBAhDQAAwIQIaQAAACZESAMAADAhQhoAAIAJEdIAAABM6P8A+f7GcLTGBXIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table, density = func_selector(G_a2q, 1)\n",
    "\n",
    "plt.figure(figsize = (10,6))\n",
    "visual.overall_features(G_a2q, table, density)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce752c76-6d7c-40cc-bc81-860f11832672",
   "metadata": {},
   "source": [
    "The vast majority of nodes have a degree close to zero, but there also many outliers which have a much higher degree than the rest, as we can appreciate in the box plot below.\n",
    "\n",
    "This suggests that most interactions are created by a small percentage of very active users. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fe677180-f2cc-44a0-b8c2-bdbd11ad0278",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plt.boxplot(density, vert=False)\n",
    "plt.xlabel(\"Degree\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5b5f0f8",
   "metadata": {},
   "source": [
    "### Functionality 2 - Find the Best users!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25fd4abe-3346-48f5-990c-29f21cec382d",
   "metadata": {},
   "source": [
    "We are now interested in computing several metrics to assess the \"importance\" – the centrality – of a node within the graph in a well defined time interval.\n",
    "\n",
    "Due to the prohibitively long execution times (especially of the betweenness centrality), we could only test the following functionalities and compare their results for short windows of time."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b49dafb1-5033-4160-a42e-975515173bbf",
   "metadata": {},
   "source": [
    "#### Betweenness"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3675c78c-b1f4-49c4-91ff-7762a8a3084d",
   "metadata": {},
   "source": [
    "The betweenness centrality measures how \"central\" a node is by finding in how many paths between all possible node pairs it appears in; in a sense, it represents how many \"communications\" between nodes it affects.\n",
    "\n",
    "Given a node $v$ in a directed and weighted graph $(V,E)$, its betweenness centrality (normalized between 0 and 1) is defined as\n",
    "\n",
    "$$\n",
    "BC(v) = \\frac{1}{(N-1)(N-2)}\\sum_{s\\neq v\\neq t\\ \\in\\ V} \\frac{\\sigma_{st}(v)}{\\sigma_{st}}\n",
    "$$\n",
    "\n",
    "where $\\sigma_{st}$ is the number of equivalent (in weight) shortest paths between a node $s$ and a node $t$, $\\sigma_{st}(v)$ is the number of those which also contain $v$ in the middle, and $N$ is the total number of nodes in the graph.\n",
    "\n",
    "**Remark:** in the case of an undirected graph it has to be multiplied by 2\n",
    "\n",
    "Sources\n",
    "- https://kops.uni-konstanz.de/bitstream/handle/123456789/5739/algorithm.pdf\n",
    "- http://aris.me/contents/teaching/data-mining-ds-2021/resources/graphs.pdf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87f1dd14-cf6e-42d9-a1a7-a8a0808205d0",
   "metadata": {},
   "source": [
    "For node $238$ in the time window `2008-08-01 / 2008-08-10` we obtained:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "id": "53b9fc31-75cc-4d69-8c94-26c9d09fc254",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Node:  238\n",
      "Time start [yyyy-mm-dd]:  2008-08-01\n",
      "Time end [yyyy-mm-dd]:  2008-08-10\n",
      "Metric [btw | pagerank | cc | dc]:  btw\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.5616119645843778"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "func_selector(G, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98bdac46-ffbb-4f3b-b1d4-223004e8efa1",
   "metadata": {},
   "source": [
    "which is quite a high value. This means that this particular user was present in many of the interactions among other users, for instance commenting/answering posts which were also commented/answered by many other users."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b6c720a-bee0-414a-8c66-29b41d5c19fc",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### PageRank"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c91fcef-2d24-4747-8b20-9df4501316b4",
   "metadata": {},
   "source": [
    "PageRank is an algorithm notably used by Google to rank web pages in search results and measure their importance.\n",
    "\n",
    "Within our context, it can be used to assign to each node a certain asymptotic probability of being reached in a large number of steps; this means that the higher this probability is, the more the node is connected to the rest and in that sense \"central\" in the graph.\n",
    "\n",
    "We can compute it by interpreting our graph as a Markov Chain and the corresponding adjacency matrix as a stochastic matrix filled with the transitional probabilities between all pairs of nodes. If we call $\\mathcal{M}$ such matrix, we can define \n",
    "$$\\hat{\\mathcal{M}} = d\\mathcal{M} + \\frac{1-d}{N}\\mathbb{1}$$\n",
    "where $d$ is a scalar called *damping factor* which is the probability that a random surfer keeps visiting the nodes, and $\\mathbb{1}$ is a matrix filled with ones with the same size of $\\mathcal{M}$.\n",
    "The stationary distribution of all nodes will be the right eigenvector corresponding to the principal eigenvalue of $\\hat{\\mathcal{M}}$, with components the limit probability – the rank – of each node.\n",
    "\n",
    "Source\n",
    "- https://en.wikipedia.org/wiki/PageRank"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12eda202-0ae3-4173-941c-6089c03abd8a",
   "metadata": {},
   "source": [
    "For node $238$ in the time window `2008-08-01 / 2008-08-31` we obtained:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "40357400-a90e-4d6d-81f9-003ee22e9756",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Node:  238\n",
      "Time start [yyyy-mm-dd]:  2008-08-01\n",
      "Time end [yyyy-mm-dd]:  2008-08-31\n",
      "Metric [btw | pagerank | cc | dc]:  pagerank\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.0007821602043691682"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "func_selector(G, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5bd9317-00db-4dd7-936d-10ffb24748aa",
   "metadata": {},
   "source": [
    "which is a very low figure. Given the graph is directed, this suggests that even though this user commented/answered many posts by other users – as we can hypothesize from its betweenness centrality – very few users in comparison commented his own posts, i.e. it's a node with many outgoing connections but not as many incoming, hence not very reachable."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63c69ed3",
   "metadata": {},
   "source": [
    "#### Closeness Centrality"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8f023aa-59b2-42d8-9472-8e6ecdd4d536",
   "metadata": {},
   "source": [
    "Closeness centrality measures how close a given node is to the rest of nodes in the graph.\n",
    "\n",
    "For a node $v$, it is a defined as\n",
    "\n",
    "$$CC(v) = \\frac{N-1}{\\sum_{u\\in V} d(u,v)}$$\n",
    "\n",
    "where $d(u,v)$ is the distance in terms of number of edges of the shortest path between $v$ and another node $u$, and $N-1$ is again needed to normalize the measure.\n",
    "\n",
    "Sources\n",
    "- https://kops.uni-konstanz.de/bitstream/handle/123456789/5739/algorithm.pdf\n",
    "- http://aris.me/contents/teaching/data-mining-ds-2021/resources/graphs.pdf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59e9d672-74fc-4149-9091-7e92281b0811",
   "metadata": {},
   "source": [
    "For node $238$ in the time window `2008-08-01 / 2008-08-31` we obtained:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "ab1bfc8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Node:  238\n",
      "Time start [yyyy-mm-dd]:  2008-08-01\n",
      "Time end [yyyy-mm-dd]:  2008-08-31\n",
      "Metric [btw | pagerank | cc | dc]:  cc\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.37043633125556547"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "func_selector(G, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef5c9af3-2c68-40eb-a51e-99bd233caf3b",
   "metadata": {},
   "source": [
    "This value reinforces what we saw earlier with the betweenness centrality: this node is \"central\" in the sense that it communicates well with others (its distance to the other nodes is \"small\")."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7548d066-79fb-48a3-8092-6ff25b97568a",
   "metadata": {},
   "source": [
    "#### Degree Centrality"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7ccf1a3-ff35-48f5-a943-1d35aad3ddef",
   "metadata": {},
   "source": [
    "The degree centrality is the simplest notion of centrality and it's defined as the (normalized) number of neighboring nodes of a given node $v$:\n",
    "\n",
    "$$DC(v)=\\frac{\\text{deg}(v)}{N-1}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6d23cc9-22a5-4da4-85af-3652de1ee232",
   "metadata": {},
   "source": [
    "For node $238$ in the time window `2008-08-01 / 2008-08-31` we obtained:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "431d1ac5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Node:  238\n",
      "Time start [yyyy-mm-dd]:  2008-08-01\n",
      "Time end [yyyy-mm-dd]:  2008-08-31\n",
      "Metric [btw | pagerank | cc | dc]:  dc\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.01826923076923077"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "func_selector(G, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45d9b8fe-87f3-4ec0-b03e-130d9fcfe95f",
   "metadata": {},
   "source": [
    "which is a low value. Given the degree centrality only measures the ratio of neighboring nodes over all possible neighbors ($N-1$), the number we got simply suggests that node $238$ it's not in a dense region of the graph (which is by itself sparse as we saw earlier)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65d50100",
   "metadata": {},
   "source": [
    "#### Visualizations\n",
    "\n",
    "Let's see 10 random neighbours of node $372$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "ffc3e080",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt = graph.plot_neighbors(G, \"372\", max_neighbors=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "630535d4",
   "metadata": {},
   "source": [
    "Now let's plot the evolution of its degree centrality over the course of 5 months:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "a1fb3ba4-e13c-4dc2-8230-8af111759c03",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Time start [yyyy-mm-dd] 2008-08-01\n",
      "Time end [yyyy-mm-dd] 2008-12-31\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt = visual.metric_evolution(G, \"372\", [\"dc\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d527df7e-fbe9-459e-bf1c-ad89c5052603",
   "metadata": {},
   "source": [
    "Its degree centrality has decreased over time: this means that as the number of nodes in the network increased its neighbors didn't increase with the same rate, hence the user is less \"central\" because it's part of a bigger community with whom he hasn't interacted much."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1236d74",
   "metadata": {},
   "source": [
    "### Functionality 3 - Shortest Ordered Route"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b339277-b254-4178-a305-70ef2b7349cd",
   "metadata": {},
   "source": [
    "By calling the function selector with the number 3 in input, it will call the functionality for the shortest ordered route.\n",
    "\n",
    "It takes in input:\n",
    "\n",
    "- An interval of time\n",
    "- A sequence of users $p = [p_2,\\dots, p_{n-1}]$\n",
    "- Initial user $p_1$ and an end user $p_n$\n",
    "\n",
    "and it returns the shortest walk that goes from user $p_j$ to $p_n$, and that visits in order the nodes in $p$.\n",
    "\n",
    "Let's see what we get by picking $p_1 = 404$, $p_n = 267$, and $p = [122,\\ 32]$, in the time interval `2008-08-01 / 2008-09-30`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "d3be7e1d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Start Node:  404\n",
      "End Node:  267\n",
      "Nodes to be visited (comma-separated):  122,32\n",
      "Time start [yyyy-mm-dd]:  2008-08-01\n",
      "Time end [yyyy-mm-dd]:  2008-09-30\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The shortest path between the two nodes that visits in order the nodes indicated is\n",
      "['404', '396', '122', '5', '32', '267']\n"
     ]
    }
   ],
   "source": [
    "shortest_ord_route = func_selector(G, 3)\n",
    "print(f\"\\nThe shortest path between the two nodes that visits in order the nodes indicated is\\n{short_ord_route}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24e6b506-5957-4a67-90ea-2d2a2e31576a",
   "metadata": {},
   "source": [
    "Now let's plot a subgraph containing these nodes and the edges between them, highlighting those in the shortest ordered path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "c043e849-f88c-4525-960c-7c47adf43114",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "route_edges = [(short_ord_route[idx], short_ord_route[idx + 1]) \n",
    "               for idx in range(len(short_ord_route) - 1)]\n",
    "\n",
    "graph.plot_subgraph(G, \n",
    "                    nodes=shortest_ord_route,\n",
    "                    highlight_edges=route_edges,\n",
    "                    highlight_color=\"blue\",\n",
    "                    figsize=(8,8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "087a8750-4c0d-4a74-b887-8ed44c203136",
   "metadata": {},
   "source": [
    "### Functionality 4 - Disconnecting graphs\n",
    "\n",
    "Calling the function selector with input 4 will start the disconnecting graphs functionality which takes in input:\n",
    "\n",
    "- Two different intervals of time (disjoint or not), which will lead to two different graphs, $G_1$ (associated to interval 1) and $G_2$ (associated to interval 2)\n",
    "- Two users which are unique to each interval of time (user_1 only appears in interval 1, while user_2 only appears in interval 2)\n",
    "\n",
    "The function returns the minimum number of links (considering their weights) required to disconnect the two users.\n",
    "\n",
    "Let's consider the time intervals `2008-08-01 / 2008-08-31` and `2008-09-01 / 2008-09-30`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "0660fb07-75da-4edb-b9d8-2ded43f43004",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Time start for the 1st interval [yyyy-mm-dd]:  2008-08-01\n",
      "Time end for the 1st interval [yyyy-mm-dd]:  2008-08-31\n",
      "Time start for the 2nd interval [yyyy-mm-dd]:  2008-09-01\n",
      "Time end for the 2nd interval [yyyy-mm-dd]:  2008-09-30\n",
      "User 1:  \n",
      "User 2:  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "A user unique to G_1 is 3261\n",
      "A user unique to G_2 is 10577\n",
      "\n",
      "The minimum number of links required to disconnect the two graphs is 4\n",
      "and the total weight of these links is 12\n"
     ]
    }
   ],
   "source": [
    "out, removed, paths = func_selector(G, 4)\n",
    "\n",
    "tot_w = sum([G[u][v][\"weight\"] for u, v in removed])\n",
    "print(f\"and the total weight of these links is {tot_w}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1614385-e873-48de-a045-d7fb95dd6247",
   "metadata": {},
   "source": [
    "Finally, let's view these links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "39645287-832b-4ee7-b7ee-46e0c4cf67d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from '/anaconda3/lib/python3.7/site-packages/matplotlib/pyplot.py'>"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph.plot_subgraph(G, nodes=list(set([node for path in paths for node in path ])), \n",
    "                    highlight_edges=removed,\n",
    "                    highlight_color='red',\n",
    "                    figsize=(10,10))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2fa070b1",
   "metadata": {},
   "source": [
    "# 4. Algorithmic question"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84645c37",
   "metadata": {},
   "source": [
    "A number n of kids are in a camp. Between some k pairs of them (a kid can be part of more than one pairs) there are often fights. At night there are two dormitories where the kids can sleep. We want, if possible, to assign each kid in one of the two dormitories in such a way that each pair of kids that fights often is assigned to a different dormitory. (There are no space problems and the two dormitories can have different number of kids.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "03978180",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 7, 32, 56]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n = [1,3,4,56,7,32,2]\n",
    "n.sort()\n",
    "n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6cf4a30c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def tuple_order(k):\n",
    "    out = []\n",
    "    for pair in k:\n",
    "        if(pair[0] > pair[1]):\n",
    "            pair = list(pair)\n",
    "            temp = pair[0]\n",
    "            pair[0] = pair[1]\n",
    "            pair[1] = temp\n",
    "            pair = tuple(pair)\n",
    "        out.append(pair)\n",
    "    return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f3fc06df",
   "metadata": {},
   "outputs": [],
   "source": [
    "# n -> list of kids\n",
    "# k -> list of pairs of kids fighting\n",
    "def dorm_algo(n, k):\n",
    "    # kids in 1st and 2nd dorm\n",
    "    dorm0 = []\n",
    "    dorm1 = []\n",
    "    # Creating a list for kids who don't get in argues\n",
    "    safe = []\n",
    "    \n",
    "    # First of all I order the list of kids...\n",
    "    n.sort()\n",
    "    # ...and the elements of the pairs using the aux function\n",
    "    k = tuple_order(k)\n",
    "    # Then I start checking\n",
    "    for pair in k:\n",
    "        if(pair[0] not in safe): # if kid0 not in safe list...\n",
    "            safe.append(pair[0]) # ...I add him...\n",
    "            dorm0.append(pair[0]) # ...and put him in dorm0\n",
    "        \n",
    "        if(pair[1] not in safe): # if kid1 not in safe list...\n",
    "            safe.append(pair[1]) # ...I add him...\n",
    "            dorm1.append(pair[1]) # ...and put him in dorm1\n",
    "            \n",
    "    # Now I check if kids from the same pairs are in the same dorm\n",
    "    # If so, I block the algorithm\n",
    "    for pair in k:\n",
    "        if(((pair[0] in dorm0) and (pair[1] in dorm0)) or (pair[0] in dorm1) and (pair[1] in dorm1)):\n",
    "            print(\"Nothing can be done!\")\n",
    "            return \n",
    "    \n",
    "    # Now is time to add the other kids in the dorms\n",
    "    for kid in n:\n",
    "        if((kid not in dorm0) and (kid not in dorm1)):\n",
    "            dorm0.append(kid)\n",
    "            \n",
    "    # Print the final dorms with the kids\n",
    "    print(\"Fighting solved! Here the dorms:\")\n",
    "    print(\"First dormitory:\", dorm0)\n",
    "    print(\"Second dormitory:\",dorm1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "454e81d4",
   "metadata": {},
   "source": [
    "Let's use as list of kids this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "51486490",
   "metadata": {},
   "outputs": [],
   "source": [
    "n = [1,2,3,4,5,6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7be921af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fighting solved! Here the dorms:\n",
      "First dormitory: [2, 1, 5, 6]\n",
      "Second dormitory: [3, 4]\n"
     ]
    }
   ],
   "source": [
    "k = [(3,2), (4,2)]\n",
    "dorm_algo(n, k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "2511e650",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nothing can be done!\n"
     ]
    }
   ],
   "source": [
    "k = [(1,3),(4,1),(3,4)] \n",
    "dorm_algo(n, k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "98f95eb0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nothing can be done!\n"
     ]
    }
   ],
   "source": [
    "k = [(5,4), (6,5), (2,6)]\n",
    "dorm_algo(n, k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9ef89133",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nothing can be done!\n"
     ]
    }
   ],
   "source": [
    "k = [(5,4), (6,5)]\n",
    "dorm_algo(n, k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d9ab7dab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nothing can be done!\n"
     ]
    }
   ],
   "source": [
    "k = [(1,3),(4,1),(3,2),(2,5),(1,2)]\n",
    "dorm_algo(n,k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1fa95158",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fighting solved! Here the dorms:\n",
      "First dormitory: [1, 2]\n",
      "Second dormitory: [3, 4, 5, 6]\n"
     ]
    }
   ],
   "source": [
    "k = [(1,3),(4,1),(3,2),(2,5),(2,6)]\n",
    "dorm_algo(n,k)"
   ]
  }
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