{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "---\n",
        "notebook_page: false\n",
        "---\n",
        "\n",
        "## PPMI over the Notes Corpus\n",
        "\n",
        "Build a positive pointwise mutual information matrix from the local Markdown corpus and inspect a small heatmap of word associations.\n"
      ]
    },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy\n",
    "import os\n",
    "import re\n",
    "from tfidf import read_markdown_files\n",
    "from collections import Counter\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "corpus = read_markdown_files(\"..\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 165 documents\n",
      "../distributed-systems/dynamo-db.md\n",
      "../distributed-systems/disconnected-operation.md\n",
      "../distributed-systems/bigtable.md\n",
      "../distributed-systems/RPC.md\n",
      "../distributed-systems/paxos-intro.md\n",
      "...\n"
     ]
    }
   ],
   "source": [
    "print(f'read {len(corpus)} documents')\n",
    "for filename in list(corpus.keys())[:5]:\n",
    "    print(f'{filename}')\n",
    "print('...')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize_text_to_words(text):\n",
    "    words = re.findall(r'\\w+', text.lower())\n",
    "    return words\n",
    "\n",
    "class Dataset:\n",
    "  \n",
    "  def __init__(self, corpus, vocab_size=10000):\n",
    "    self.corpus = {\n",
    "      p: self.normalize(t) for p, t in corpus.items()\n",
    "    }\n",
    "    self.path_list = list(self.corpus.keys())\n",
    "    self._path_to_idx = {path: i for i, path in enumerate(self.path_list)}\n",
    "    self.vocab = set()\n",
    "    self.word_to_idx = {}\n",
    "    self.idx_to_word = {}\n",
    "    self.vocab_size = vocab_size\n",
    "    self._build_vocab()\n",
    "    self._remove_unk()\n",
    "\n",
    "  def normalize(self, text):\n",
    "    return normalize_text_to_words(text)\n",
    "  \n",
    "  def _build_vocab(self):\n",
    "    word_counts = Counter()\n",
    "    for path, words in self.corpus.items():\n",
    "      word_counts.update(words)\n",
    "      \n",
    "    # remove words that are shorter than 3 characters\n",
    "    for word in list(word_counts.keys()):\n",
    "      if len(word) < 3:\n",
    "        del word_counts[word]\n",
    "        \n",
    "    top_k_words = [word for word, _ in word_counts.most_common(self.vocab_size)]\n",
    "    self.vocab = set(top_k_words)\n",
    "    self.word_to_idx = {word: i for i, word in enumerate(self.vocab)}\n",
    "    self.idx_to_word = {i: word for i, word in enumerate(self.vocab)}\n",
    "    \n",
    "  def _remove_unk(self):\n",
    "    self.corpus = {\n",
    "      p: [w for w in words if w in self.vocab] for p, words in self.corpus.items()\n",
    "    }\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class PPMIMatrix:\n",
    "\n",
    "    def __init__(self, dataset, context_size=20):\n",
    "        self.dataset = dataset\n",
    "        self._context_size = context_size\n",
    "        self.V = len(dataset.vocab)\n",
    "        self.X = numpy.zeros((self.V, self.V))\n",
    "        \n",
    "        self.N = 0\n",
    "        # For each position, count valid context positions\n",
    "        for words in dataset.corpus.values():\n",
    "            for i in range(len(words)):\n",
    "                # sure, you could optimize with math, but this isn't a bottleneck\n",
    "                for j in range(i - context_size, i + context_size + 1):\n",
    "                    if j >= 0 and j < len(words) and j != i:\n",
    "                        self.N += 1\n",
    "        self._build_cooccurrence_matrix()\n",
    "        self._build_ppmi_matrix()\n",
    "\n",
    "    def _build_cooccurrence_matrix(self):\n",
    "        for path, words in self.dataset.corpus.items():\n",
    "            for i, word in enumerate(words):\n",
    "                word_idx = self.dataset.word_to_idx[word]\n",
    "                for j in range(i - self._context_size, i + self._context_size + 1):\n",
    "                    if j >= 0 and j < len(words) and j != i:\n",
    "                        context_word = words[j]\n",
    "                        context_word_idx = self.dataset.word_to_idx[context_word]\n",
    "                        self.X[word_idx, context_word_idx] += 1\n",
    "\n",
    "    def _build_ppmi_matrix(self):\n",
    "        self.P = numpy.zeros((self.V, self.V))\n",
    "\n",
    "        epsilon = 1e-10\n",
    "\n",
    "        for i in range(self.V):\n",
    "            for j in range(self.V):\n",
    "                if self.X[i, j] > 0:\n",
    "                    pmi = numpy.log2(\n",
    "                        (self.X[i, j] * self.N)\n",
    "                        / ((self.X[i].sum() + epsilon) * (self.X[:, j].sum() + epsilon))\n",
    "                    )\n",
    "                    self.P[i, j] = max(0, pmi)\n",
    "\n",
    "    def get_ppmi(self, word1, word2):\n",
    "        i = self.dataset.word_to_idx[word1]\n",
    "        j = self.dataset.word_to_idx[word2]\n",
    "        return self.P[i, j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'choice', 'managed', 'vpn', 'ranges', 'abort', 'instead', 'max_delay', 'writing', 'tokens', 'converts', 'configurable', 'kinds', 'exclusion', 'papers', 'converting', 'event_type', 'esp', 'resistor', 'val', 'finish', 'diagonalizable', 'degree', 'collapse', 'well', 'exp', 'refresh', 'r_2', 'closer', 'versa', 'study', 'allows', 'provide', '360859', 'sts', 'membership', 'reflect', 'google', 'doing', 'leader', 'stalls', 'odd', 'repair', 'show', 'named', 'directly', 'roommate', 'elsewhere', 'variant', 'triggers', 'schedules', 'tag', 'compromise', 'delayed', 'retransmission', 'omega', 'bins', 'dc_i', 'dividing', 'satisfy', 'spatial', 'battery', 'spades', 'java', 'integers', 'attempts', 'goes', 'pitfall', 'identifier', 'analyzing', 'creation', 'restrict', 'sources', 'special', 'spend', 'overhead', 'truth', 'cross', 'subproblems', 'consensus', 'friendly', 'garbage', 'namespace', 'document', 's_2', 'internet', 'become', 'mount', 'bigtable', 'incorrectly', 'hamming', 'digital', 'rts', 'clientinput', 'said', 'online', 'focusing', 'parties', 'milli', 'belt', 'video', 'neck', 'exit', 'holds', 'netdb', 'nonzero', 'plt', 'mod', 'template', 'sessions', 'described', 'packet', 'cp_brute_force', 'other', 'copyright', 'covering', 'ownership', 'w_n', 'committed', 'angles', 'traffic', 'embeddings', 'relay', 'zero', 'dijkstra', 'recover', 'unidirectional', 'each', 'corner', 'exceeded', 'depending', 'would', 'laws', 'desired', 'failed', 'round', 'defaultdict', 'snapshots', 'thread', 'retransmit', 'a_x', 'fixed', 'rectangle', 'browsers', 'segments', 'invoking', 'assumed', 'pre', 'older', 'uses', 'engineers', 'frameworks', 'threading', 'putsome', 'student', 'rpcs', 'delivers', 'necessarily', 'innovation', 'echelon', 'usage', 'expected_frame', 'feature', 'are', 'lossless', 'applying', '180', 'constrained', 'layers', 'oltp', 'transformations', 'abandon', 'sin_addr', 'isolate', 'development', 'window_size', 'takes', 'scalable', 'adjacent', 'sparser', 'inherent', 'holding', 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'regular', 'authentication', 'router', 'philosophy', 'divisible', 'changed', 'modern', 'products', 'acid', 'likely', 'p_i', 'u_3', 'giant', 'mismatch', 'mask', 'callee', 'inductor', 'behave', 'existence', 'atomic', 'beta', 'b_j', 'v_j', 'prevents', 'limits', 'notify', 'programmer', 'chess', 'feedback', 'written', 'boil', 'refer', 'organization', 'abstractly', 'fault', 'bottleneck', 'passband', 'completes', 'peek', 'shifts', 'max_routes', 'variables', 'elif', 'primitive', 'b_m', 'public', 'consumers', 'mounted', 'optimizes', 'regions', 'transport', 'properly', 'privilege', 'request', 'amperes', 'reads', 'merge', 'declares', 'child', 'illinois', 'block', 'solve', 'root', 'actual', 'implements', 'regularly', 'obtaining', 'diagrams', 'delivering', 'intensive', 'a_2x_2', 'generates', 'azurewebsites', 'abstractions', 'all_c', 'seconds', 'arraylist', 'multiplex', 'everything', 'suppose', 'generation', 'sockaddr', 'delta_', 'fair', 'reboot', 'nothing', 'classification', 'mode', 'wireless', 'metrics', 'drivers', 'frame', 'preprocessing', 'managing', 'similar', 'composed', 'emptyset', 'basis', 'correction', 'forcing', 'projection', 'deg', 'compression', 'due', 'csma', 'coordinates', 'systemsapproach', 'clientip', 'intel', 'consumed', 'passing', 'collection', 'e_t', 'reflection', 'works', 'decrement', 'continuing', 'dedicated', 'shown', 'leaf', 'shrinks', 'modifying', 'corrupting', 'midpoint', 'partitioning', 'heterogeneous', 'splitting', 'passed', 'benches', 'sampling', 'underlying', 'trap_ret', 'nrz', 'creates', 'around', 'interesting', 'has', 'registers', 'doesn', 'boils', 'base', 'bare', 'overwrite', 'disclaimers', 'knights', 'stdlib', 'frequency', 'offers', 'placed', 'runaway', 'lru', 'possible_left_halfs', 'org', 'solving', 'models', 'publish', 'introduction', 'p_n', 'circular', 'cluster', 'stability', 'f_i', 'certainly', 'classes', 'amps', 'infer', 'quality', 'inif', 'connected_components', 'kappa', 'keyword', 'highcontdoc2', 'inductors', 'losing', 'prioritizes', 'y_n'}\n",
      "['dynamo', 'amazon', 'highly', 'available', 'key', 'value', 'store', 'reading', 'https', 'acm', 'org', 'lib', 'washington', 'edu', 'pdf', 'dynamo', 'highly', 'available', 'key', 'value', 'storage', 'system', 'that', 'consistency', 'under', 'certain', 'failure', 'conditions', 'making', 'extensive', 'use', 'object', 'versioning', 'and', 'application', 'conflict', 'resolution']\n",
      "vocabulary size: 5000\n",
      "word_to_idx: [('choice', 0), ('managed', 1), ('vpn', 2), ('ranges', 3), ('abort', 4)]\n"
     ]
    }
   ],
   "source": [
    "ds = Dataset(corpus, vocab_size=5000)\n",
    "print(ds.vocab)\n",
    "print(list(ds.corpus.values())[0])\n",
    "print(f'vocabulary size: {len(ds.vocab)}')\n",
    "print(f'word_to_idx: {list(ds.word_to_idx.items())[:5]}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ppmim = PPMIMatrix(ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_pmim_heatmap(ppmim, words):\n",
    "  plt.figure(figsize=(10, 10))\n",
    "  plt.imshow(ppmim.P, cmap='hot', interpolation='nearest')\n",
    "  plt.colorbar()\n",
    "  plt.show()\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_pmim_heatmap(ppmim, list(ds.vocab))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "nlp.venv",
   "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": "3.13.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}