{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": ["# Experiment 04 — Perplexity Comparison Table\n", "Collects results from all ablations and renders a comparison table."]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Fill these in after running experiments 01-03\n",
    "results = {\n",
    "    'Model': ['Vanilla Transformer', 'Mesh Attention Only', 'Full TMT'],\n",
    "    'Perplexity': [None, None, None],   # replace with actual values\n",
    "    'Avg Compute / Token': ['100%', '~60%', '~50%'],\n",
    "    'Innovations': [\n",
    "        'none',\n",
    "        'mesh attention',\n",
    "        'mesh + temporal decay + adaptive depth + dual-stream FFN + memory anchors'\n",
    "    ]\n",
    "}\n",
    "\n",
    "df = pd.DataFrame(results)\n",
    "print(df.to_markdown(index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "valid = [(m, p) for m, p in zip(results['Model'], results['Perplexity']) if p is not None]\n",
    "if valid:\n",
    "    models, ppls = zip(*valid)\n",
    "    bars = ax.bar(models, ppls, color=['#4C72B0', '#DD8452', '#55A868'])\n",
    "    ax.bar_label(bars, fmt='%.1f')\n",
    "    ax.set_ylabel('Perplexity (lower is better)')\n",
    "    ax.set_title('TemporalMesh Transformer Ablation Study')\n",
    "    plt.tight_layout()\n",
    "    plt.savefig('ablation_perplexity.png', dpi=150)\n",
    "    plt.show()\n",
    "else:\n",
    "    print('Run experiments 01-03 first, then fill in the Perplexity values above.')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"},
  "language_info": {"name": "python", "version": "3.10.0"}
 },
 "nbformat": 4,
 "nbformat_minor": 4
}