heterogeneous_graphlets 0.1.1

A Rust library for the computation of heterogeneous graphlets.
Documentation
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6ab2335c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f7db5c05",
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = pd.read_csv(\"tests/data/citeseer/nodes.tsv\", sep=\"\\t\")[[\"node_type\"]]\n",
    "labels.to_csv(\"tests/data/citeseer/node_list.csv\", header=None, index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "a5657bca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "node_type\r\n",
      "Agents\r\n",
      "IR\r\n",
      "DB\r\n",
      "AI\r\n",
      "HCI\r\n",
      "ML\r\n",
      "Word\r\n",
      "Unknown\r\n"
     ]
    }
   ],
   "source": [
    "!head /bfd/graphs/linqs/CiteSeer/latest/preprocessed/undirected/733d2a25a673d8b777ecd366efd2cef45483474937ae74abfe53ef1cdd791b6d/node_types.tsv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "df8e68b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "edges = pd.read_csv(\"tests/data/citeseer/edges.tsv\", sep=\"\\t\", header=None)[[0, 1]]\n",
    "#labels.to_csv(\"tests/data/citeseer/edge_list.csv\", header=None, index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "81f44615",
   "metadata": {},
   "outputs": [],
   "source": [
    "edges[((edges < 3312).all(axis=1)) & (edges[0] != edges[1])].to_csv(\"tests/data/citeseer/edge_list.csv\", header=None, index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fb766d80",
   "metadata": {},
   "outputs": [],
   "source": [
    "edges = pd.read_csv(\"tests/data/cora/edge_list.csv\", header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "720ec18a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3412"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "12 * 4**4 + 4**4+ 4**3 + 4**2 + 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f3623a4d",
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "index 4140 is out of bounds for axis 0 with size 4140",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_2466193/876094773.py\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0medges\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0medges\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m7\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m: index 4140 is out of bounds for axis 0 with size 4140"
     ]
    }
   ],
   "source": [
    "edges[labels.values[edges[0]] == 7]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "780c2e3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "edges[(edges < 2708).all(axis=1)].to_csv(\"tests/data/cora/edge_list.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "83f569aa",
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "index 4140 is out of bounds for axis 0 with size 4140",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_2466193/471396866.py\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlabels\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0medges\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m7\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m: index 4140 is out of bounds for axis 0 with size 4140"
     ]
    }
   ],
   "source": [
    "labels.values[edges[0]] == 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "26edc03f",
   "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>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108985</th>\n",
       "      <td>4140</td>\n",
       "      <td>1772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108986</th>\n",
       "      <td>4140</td>\n",
       "      <td>1859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108987</th>\n",
       "      <td>4140</td>\n",
       "      <td>1894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108988</th>\n",
       "      <td>4140</td>\n",
       "      <td>2228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108989</th>\n",
       "      <td>4140</td>\n",
       "      <td>2400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>108990 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           0     1\n",
       "0          0     1\n",
       "1          0     1\n",
       "2          0     8\n",
       "3          0    14\n",
       "4          0   258\n",
       "...      ...   ...\n",
       "108985  4140  1772\n",
       "108986  4140  1859\n",
       "108987  4140  1894\n",
       "108988  4140  2228\n",
       "108989  4140  2400\n",
       "\n",
       "[108990 rows x 2 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a942bcbc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}