growing_benchmark.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "custom_growing_result = [258.990966796875, 121.43310546875, 79.761962890625, 76.5029296875, 79.4638671875, 81.035888671875, 68.123046875, 66.65087890625, 70.01806640625, 78.943115234375]\n",
    "builtin_growing_result = [1.547119140625, 0.761962890625, 0.375, 0.73388671875, 0.55517578125, 0.742919921875, 0.865966796875, 0.705078125, 0.30810546875, 0.6650390625]\n",
    "\n",
    "plt.boxplot([custom_growing_result, builtin_growing_result], labels=['custom', 'builtin'])\n",
    "plt.ylabel('runtime (ms)')\n",
    "plt.title('runtime of custom vs builtin growing')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.10.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}