cluster.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to /home/bumblebee/nltk_data...\n[nltk_data]   Package punkt is already up-to-date!\n[nltk_data] Downloading package stopwords to\n[nltk_data]     /home/bumblebee/nltk_data...\n[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "import sys\n",
    "from collections import defaultdict\n",
    "from os import cpu_count, walk, path\n",
    "from typing import List, Tuple\n",
    "\n",
    "import nltk\n",
    "import pandas as pd\n",
    "from gensim.models.doc2vec import TaggedDocument, Doc2Vec\n",
    "from matplotlib import pyplot as plt\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem.porter import PorterStemmer\n",
    "from numpy import ndarray\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "import conf\n",
    "\n",
    "csvfile = '../Semantic-Analysis-Regulations/regulations_data_analysis.csv'\n",
    "doc2vec_model_name = 'doc2vec_model_{}'.format(conf.DATA_SOURCE)\n",
    "\n",
    "nltk.download('punkt')\n",
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def tokenize(text: str) -> List[str]:\n",
    "    # Tokenize\n",
    "    tokenized_text: List[str] = nltk.word_tokenize(text)\n",
    "\n",
    "    # Remove unwanted words (numbers and stopwords)\n",
    "    stops: List[str] = stopwords.words('english')\n",
    "    # TODO: Do we need to filter out numbers?\n",
    "    tokenized_text: List[str] = [token for token in tokenized_text\n",
    "                                  if re.match(r'.*[A-Za-z].*', token)\n",
    "                                  and token not in stops]\n",
    "\n",
    "    # Stemming\n",
    "    # https://www.nltk.org/api/nltk.stem.html#module-nltk.stem.porter\n",
    "    stemmer = PorterStemmer()\n",
    "    return [stemmer.stem(token) for token in tokenized_text]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def build_model(documents: List[str]) -> None:\n",
    "    print('Building Doc2Vec model')\n",
    "\n",
    "    model = Doc2Vec(vector_size=conf.VECTOR_SIZE,\n",
    "                    window=conf.WINDOW,\n",
    "                    min_count=conf.MIN_COUNT,\n",
    "                    workers=cpu_count() - 1,\n",
    "                    epochs=conf.EPOCHS)\n",
    "    model.build_vocab(documents)\n",
    "    model.train(documents,\n",
    "                total_examples=len(documents),\n",
    "                epochs=model.iter)\n",
    "    model.save(doc2vec_model_name)\n",
    "    \n",
    "def load_model() -> Doc2Vec:\n",
    "    return Doc2Vec.load(doc2vec_model_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cluster() -> Tuple[KMeans, ndarray]:\n",
    "    kmeans_model = KMeans(n_clusters=conf.N_CLUSTERS,\n",
    "                          n_jobs=-1,\n",
    "                          #verbose=True\n",
    "                          )\n",
    "    colors = kmeans_model.fit_predict(load_model().docvecs.vectors_docs)\n",
    "    return (kmeans_model, colors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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     ]
    }
   ],
   "source": [
    "documents: List[TaggedDocument] = []\n",
    "tags: List[str] = []\n",
    "if conf.DATA_SOURCE == 'long_title':\n",
    "    with open(csvfile, 'r') as f:\n",
    "        df = pd.read_csv(f)\n",
    "        tags = long_titles = df['long_title']\n",
    "    documents = [TaggedDocument(doc, [i])\n",
    "                 for i, doc in enumerate([tokenize(title)\n",
    "                                          for title in long_titles])]\n",
    "elif conf.DATA_SOURCE == 'full_text':\n",
    "    for root, _, files in walk('txt'):\n",
    "        tags = sorted(files)\n",
    "        for i, name in enumerate(tags):\n",
    "            print('Loading file {}'.format(name))\n",
    "            with open(path.join(root, name), 'r') as f:\n",
    "                documents.append(TaggedDocument(tokenize(f.read()), [i]))\n",
    "        break\n",
    "else:\n",
    "    print('Invalid data source')\n",
    "    sys.exit(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Building Doc2Vec model\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/bumblebee/Documents/UROP/code/venv/lib64/python3.6/site-packages/ipykernel_launcher.py:12: DeprecationWarning: Call to deprecated `iter` (Attribute will be removed in 4.0.0, use self.epochs instead).\n  if sys.path[0] == '':\n"
     ]
    }
   ],
   "source": [
    "build_model(documents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "kmeans_model, colors = cluster()\n",
    "centers = kmeans_model.cluster_centers_\n",
    "\n",
    "df = pd.DataFrame(sorted(list(zip(colors, tags)), key=lambda x: x[0]))\n",
    "\n",
    "df.to_pickle('data_frame_{}'.format(conf.DATA_SOURCE))\n",
    "df.to_csv('cluster_result_{}.csv'.format(conf.DATA_SOURCE),\n",
    "          index=False)\n",
    "\n",
    "# print(centers)\n",
    "# print(kmeans_model.labels_)\n",
    "\n",
    "# Got multi-dimensional vectors in the result. Project to plot\n",
    "pca_2d = PCA(n_components=2).fit_transform(load_model().docvecs.vectors_docs)\n",
    "plt.scatter(pca_2d[:, 0], pca_2d[:, 1],\n",
    "            c=colors,\n",
    "            picker=True)\n",
    "plt.scatter(centers[:, 0], centers[:, 1],\n",
    "            c='black',\n",
    "            s=100,\n",
    "            alpha=0.3)\n",
    "\n",
    "plt.savefig('cluster_plot.svg',\n",
    "            format='svg')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "language": "python"
 },
 "nbformat": 4,
 "nbformat_minor": 2
}