70 lines
2.0 KiB
Plaintext
70 lines
2.0 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "imports",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"from pyprojroot import here"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "load",
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"metadata": {},
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"outputs": [],
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"source": [
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"data = pd.read_csv(here() / 'data/base/data.csv')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "plot",
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"metadata": {},
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"outputs": [],
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"source": [
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"fig, ax = plt.subplots(figsize=(10, 6))\n",
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"\n",
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"# Color by detector type\n",
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"colors = {'APD': 'steelblue', 'SNSPD': 'coral', 'PMT': 'green', 'SPAD': 'purple'}\n",
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"for detector in data['Detector Type'].unique():\n",
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" mask = data['Detector Type'] == detector\n",
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" ax.scatter(data[mask]['Distance (m)'], data[mask]['Visibility (%)'],\n",
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" label=detector, alpha=0.7, s=100, color=colors.get(detector, 'gray'),\n",
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" edgecolors='black', linewidth=1)\n",
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"\n",
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"# Fit and plot trend line\n",
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"z = np.polyfit(data['Distance (m)'], data['Visibility (%)'], 1)\n",
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"p = np.poly1d(z)\n",
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"x_trend = np.linspace(data['Distance (m)'].min(), data['Distance (m)'].max(), 100)\n",
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"ax.plot(x_trend, p(x_trend), 'r--', linewidth=2, alpha=0.5, label=f'Trend (slope={z[0]:.2f})')\n",
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"\n",
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"ax.set_xlabel('Photon Pair Distance (m)', fontsize=12)\n",
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"ax.set_ylabel('Visibility (%)', fontsize=12)\n",
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"ax.set_title('Visibility vs. Photon Pair Distance', fontsize=14)\n",
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"ax.legend(loc='best')\n",
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"ax.grid(True, alpha=0.3)\n",
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"\n",
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"plt.tight_layout()\n",
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"plt.savefig(here() / 'output/plots/visibility_distance.png', dpi=300, bbox_inches='tight')"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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