64 lines
9.5 KiBLFS
Plaintext
64 lines
9.5 KiBLFS
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 1,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import numpy as np\n",
|
|
"from scipy.optimize import curve_fit\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"import plotly.graph_objects as go\n",
|
|
"plt.rcParams['font.family'] = 'Arial'"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": "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",
|
|
"text/plain": [
|
|
"<Figure size 100x100 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"fig = plt.figure(figsize=(1, 1))\n",
|
|
"ax = fig.gca()\n",
|
|
"# ax.set_title(\"$\\\\mathrm{x(zy)\\\\overline{x}}$\", fontsize=10, fontname='Arial')\n",
|
|
"ax.set_title(\"$\\\\mathrm{E_2}$-4\", fontsize=10, fontname='Arial')\n",
|
|
"fig.text(-0.03, 0.5, \"Raman intensity\\n(log, a.u.)\", va='center', ha='center', rotation='vertical', fontsize=12, fontname='Arial')\n",
|
|
"fig.savefig(f'画图/文字/文字.svg', format='svg', transparent=True, bbox_inches='tight')"
|
|
]
|
|
}
|
|
],
|
|
"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": "3.13.9"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|