{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "imports",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from pyprojroot import here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "load",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(here() / 'data/base/data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "plot",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "# Histogram of fidelity\n",
    "ax1.hist(data['Entanglement Fidelity'], bins=15, color='coral', alpha=0.7, edgecolor='black')\n",
    "ax1.set_xlabel('Entanglement Fidelity', fontsize=12)\n",
    "ax1.set_ylabel('Frequency', fontsize=12)\n",
    "ax1.set_title('Distribution of Entanglement Fidelity', fontsize=13)\n",
    "ax1.grid(True, alpha=0.3)\n",
    "\n",
    "# Category pie chart\n",
    "category_counts = data['Fidelity Category'].value_counts()\n",
    "colors = ['#2ecc71', '#3498db', '#f39c12', '#e74c3c']\n",
    "ax2.pie(category_counts.values, labels=category_counts.index, autopct='%1.1f%%',\n",
    "        colors=colors, startangle=90)\n",
    "ax2.set_title('Fidelity Categories', fontsize=13)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(here() / 'output/plots/fidelity_dist.png', dpi=300, bbox_inches='tight')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
