Initial

notebooks/plot_fidelity_dist.ipynb

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+{
+ "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
+}