2025-07-13 08:55:18 +08:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-06T07:29:51.887474Z",
"start_time": "2023-05-06T07:29:45.336311Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"E:\\Pycharm\\Anaconda3\\lib\\site-packages\\requests\\__init__.py:89: RequestsDependencyWarning: urllib3 (1.26.15) or chardet (3.0.4) doesn't match a supported version!\n",
" warnings.warn(\"urllib3 ({}) or chardet ({}) doesn't match a supported \"\n"
]
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"# 导入matplotlib的pyplot模块用于数据可视化。\n",
"import tensorflow as tf\n",
"# 导入tensorflow库用于深度学习模型的构建和训练\n",
"from vmdpy import VMD \n",
"# 从vmdpy库导入VMD用于变分模态分解\n",
"import pandas as pd\n",
"# 导入pandas库用于数据处理和分析\n",
"import warnings\n",
"# 导入warnings库用于控制警告消息\n",
"warnings.filterwarnings(\"ignore\")\n",
"# 设置忽略警告消息,通常用于减少输出中的不必要警告"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-06T07:30:07.694017Z",
"start_time": "2023-05-06T07:30:06.640539Z"
}
},
"outputs": [],
"source": [
"# 调用GPU加速\n",
"gpus = tf.config.experimental.list_physical_devices(device_type='GPU')\n",
"for gpu in gpus:\n",
" tf.config.experimental.set_memory_growth(gpu, True)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-06T07:30:10.114152Z",
"start_time": "2023-05-06T07:30:10.110150Z"
}
},
"outputs": [],
"source": [
"# 用来正常显示中文标签\n",
"plt.rcParams['font.sans-serif'] = ['Times New Roman']\n",
"# 用来正常显示负号\n",
"plt.rcParams['axes.unicode_minus'] = False"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-06T07:30:11.964131Z",
"start_time": "2023-05-06T07:30:11.924656Z"
}
},
"outputs": [],
"source": [
"df_raw_data = pd.read_csv('农林牧渔.csv', usecols=[0,1], encoding='gbk')\n",
"# 使用pandas的read_csv函数读取CSV文件。\n",
"# '农林牧渔.csv'是文件名。\n",
"# usecols=[0,1]指定只读取CSV文件的第一列和第二列。\n",
"# encoding='gbk'指定文件编码格式为GBKGBK常用于中文字符编码。\n",
"series_close = pd.Series(df_raw_data['收盘指数'].values, index=df_raw_data['发布日期'])\n",
"# 创建一个pandas的Series对象。\n",
"# df_raw_data['收盘指数'].values提取'收盘指数'列的值作为Series的数据。\n",
"# index=df_raw_data['发布日期']设置Series的索引为'发布日期'列的值。"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"发布日期\n",
"2022/5/20 0:00 3259.34\n",
"2022/5/19 0:00 3234.45\n",
"2022/5/18 0:00 3262.52\n",
"2022/5/17 0:00 3267.97\n",
"2022/5/16 0:00 3305.64\n",
" ... \n",
"2000/1/7 0:00 1106.19\n",
"2000/1/6 0:00 1065.67\n",
"2000/1/5 0:00 1028.87\n",
"2000/1/4 0:00 1027.66\n",
"1999/12/30 0:00 1000.00\n",
"Length: 5406, dtype: float64\n"
]
}
],
"source": [
"print(series_close)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x432 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def vmd_decompose(series=None, num_modes=3, alpha=2000, tau=0, K=3, DC=1, init=1, tol=1e-7):\n",
" # 定义变分模态分解VMD函数具有多个参数。\n",
" # series待分解的时间序列。\n",
" # num_modes分解的模态数量。\n",
" # alpha, tau, K, DC, init, tolVMD算法的参数。\n",
"\n",
" decom = VMD(series.values, alpha=alpha, tau=tau, K=K, DC=DC, init=init, tol=tol)\n",
" # 使用VMD方法对输入的时间序列进行分解。\n",
"\n",
" vmd_result, *_ = decom\n",
" # 从VMD返回的结果中获取分解后的模态。\n",
"\n",
" df_vmd = pd.DataFrame(vmd_result.T)\n",
" # 将分解后的模态转换为DataFrame。\n",
"\n",
" df_vmd.columns = ['imf' + str(i) for i in range(len(df_vmd.columns))]\n",
" # 为DataFrame的每一列命名表示每个模态。\n",
"\n",
" df_vmd.to_csv('vmd_decompose.csv')\n",
" # 将分解结果保存到CSV文件中。\n",
"\n",
" return df_vmd\n",
" # 返回分解结果。\n",
"\n",
"# 调用函数并传入参数\n",
"df_vmd_result = vmd_decompose(series=series_close, num_modes=3, alpha=2000, tau=0, K=3, DC=1, init=1, tol=1e-7)\n",
"# 使用vmd_decompose函数对series_close进行VMD分解。\n",
"\n",
"# 可视化VMD分解结果\n",
"fig, axs = plt.subplots(nrows=len(df_vmd_result.columns), figsize=(10, 6), sharex=True)\n",
"# 创建一个绘图对象和多个子图对象。\n",
"\n",
"for i, col in enumerate(df_vmd_result.columns):\n",
" axs[i].plot(df_vmd_result[col])\n",
" axs[i].set_title(col)\n",
" # 遍历每个模态并绘制在子图上。\n",
"\n",
"plt.suptitle('VMD Decomposition')\n",
"# 设置图表的总标题。\n",
"\n",
"plt.xlabel('Time')\n",
"# 设置x轴的标签。\n",
"\n",
"plt.show()\n",
"# 显示图表。\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-06T07:57:47.266426Z",
"start_time": "2023-05-06T07:57:47.245421Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" imf0 imf1 imf2\n",
"0 3531.751521 -191.760606 -97.465751\n",
"1 3531.473729 -191.684118 -97.693419\n",
"2 3531.227653 -191.210280 -97.722481\n",
"3 3530.660421 -190.706280 -97.838212\n",
"4 3529.466722 -190.488685 -98.200846\n",
"... ... ... ...\n",
"5401 1400.221164 -285.714281 -40.909098\n",
"5402 1398.327887 -289.990072 -43.032448\n",
"5403 1396.429155 -293.765904 -45.520341\n",
"5404 1395.016313 -296.474920 -47.544327\n",
"5405 1394.130730 -298.027741 -48.828768\n",
"\n",
"[5406 rows x 3 columns]\n"
]
}
],
"source": [
"print(df_vmd_result)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-06T08:20:56.821052Z",
"start_time": "2023-05-06T08:20:52.877404Z"
}
},
"outputs": [],
"source": [
"df_vmd_result.to_excel(\"VMD.xlsx\",index=False)#保存数据为VMD.xlsx"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.8.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}