the

.idea/.gitignore

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+# 默认忽略的文件
+/shelf/
+/workspace.xml

.idea/AirQuility.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="jdk" jdkName="Python 3.11 (AirQuilitySys)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="PyDocumentationSettings">
+    <option name="format" value="PLAIN" />
+    <option name="myDocStringFormat" value="Plain" />
+  </component>
+  <component name="TestRunnerService">
+    <option name="PROJECT_TEST_RUNNER" value="py.test" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.11 (AirQuilitySys)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (AirQuilitySys)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/AirQuility.iml" filepath="$PROJECT_DIR$/.idea/AirQuility.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="" vcs="Git" />
+  </component>
+</project>

AirQuilitySys/.idea/.gitignore

@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml

AirQuilitySys/.idea/AirQuilitySys.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

AirQuilitySys/.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

AirQuilitySys/.idea/misc.xml

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.11 (AirQuilitySys)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (AirQuilitySys)" project-jdk-type="Python SDK" />
+</project>

AirQuilitySys/.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/AirQuilitySys.iml" filepath="$PROJECT_DIR$/.idea/AirQuilitySys.iml" />
+    </modules>
+  </component>
+</project>

AirQuilitySys/.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$/.." vcs="Git" />
+  </component>
+</project>

AirQuilitySys/AirQui.py

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+import tkinter as tk
+import subprocess
+import sys
+
+def run_DayAir():
+    """函数用于执行另一个Python脚本"""
+    try:
+        subprocess.run(["D:\Pycharm\Project\AirQuilitySys\.venv\Scripts\python.exe", "DayAir.py"], check=True)
+    except subprocess.CalledProcessError as e:
+        print(f"执行脚本时发生错误: {e}")
+
+def run_DayAirzhu():
+    """函数用于执行另一个Python脚本"""
+    try:
+        subprocess.run(["D:\Pycharm\Project\AirQuilitySys\.venv\Scripts\python.exe", "DayAirzhu.py"], check=True)  # 尝试运行另一个Python脚本
+    except subprocess.CalledProcessError as e:
+        print(f"执行脚本时发生错误: {e}")
+
+def run_DayAirbing():
+    """函数用于执行另一个Python脚本"""
+    try:
+        subprocess.run(["D:\Pycharm\Project\AirQuilitySys\.venv\Scripts\python.exe", "DayAirbing.py"], check=True)  # 尝试运行另一个Python脚本
+    except subprocess.CalledProcessError as e:
+        print(f"执行脚本时发生错误: {e}")
+
+def run_time():
+    """函数用于执行另一个Python脚本"""
+    try:
+        subprocess.run(["D:\Pycharm\Project\AirQuilitySys\.venv\Scripts\python.exe", "time.py"], check=True)  # 尝试运行另一个Python脚本
+    except subprocess.CalledProcessError as e:
+        print(f"执行脚本时发生错误: {e}")
+
+# 创建主窗口
+window = tk.Tk()
+window.title("执行外部程序示例")
+
+# 创建一个按钮，点击时调用run_another_program函数
+but = tk.Button(window, text="查看每日空气折线分布图", command=run_DayAir)
+but.pack(padx=20, pady=20)  # 设置按钮布局
+
+butt = tk.Button(window, text="查看每日空气柱状图", command=run_DayAirzhu)
+butt.pack(padx=20, pady=20)  # 设置按钮布局
+
+butto = tk.Button(window, text="查看每月pm2.5平均指数", command=run_DayAirbing)
+butto.pack(padx=20, pady=20)  # 设置按钮布局
+
+bu = tk.Button(window, text="查看未来预测数据", command=run_time)
+bu.pack(padx=20, pady=20)  # 设置按钮布局
+# 运行Tkinter事件循环
+window.mainloop()

AirQuilitySys/DayAir.py

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+import logging
+import pymysql
+import subprocess
+import numpy as np
+from matplotlib import pyplot as plt
+from tkinter import Tk
+from pyecharts import options as _opts
+from pyecharts.charts import Bar
+
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+def get_data(db_config):
+    """
+    从数据库中获取ptime和ci数据。
+    :param db_config: 数据库配置字典
+    :return: 包含ptime和ci的元组列表
+    """
+    ptime_list = []  # 存储ptime数据的列表
+    ci_list = []  # 存储ci数据的列表
+    so_list = []
+
+
+    try:
+        with pymysql.connect(**db_config) as conn:
+            logging.info("数据库连接成功")
+            with conn.cursor() as cursor:
+                # 使用单个查询以提高性能
+                sql_ptime = "SELECT ptime FROM May"
+                cursor.execute(sql_ptime)
+                data_ptime = cursor.fetchall()
+                #print(data_ptime)
+                # 处理查询结果
+                #for row in data:
+                    #for row in range(len(data)):
+                        #if row == 0:
+                            #continue
+                   # print(row)
+
+                ptime_list = [row['ptime'] for row in data_ptime if 'ptime' in row]
+                #row_list=[val for sublist in row for val in sublist]
+
+                sql_ci="SELECT ci FROM may"
+                cursor.execute(sql_ci)
+                data_ci=cursor.fetchall()
+                #print(data_ci)
+                ci_list = [row['ci'] for row in data_ci if 'ci' in row]
+
+                sql_so = "SELECT so FROM may"
+                cursor.execute(sql_so)
+                data_so = cursor.fetchall()
+                so_list = [row['so'] for row in data_so if 'so' in row]
+
+                sql_no = "SELECT no FROM may"
+                cursor.execute(sql_no)
+                data_no = cursor.fetchall()
+                no_list = [row['no'] for row in data_no if 'no' in row]
+
+                sql_pm = "SELECT pm FROM may"
+                cursor.execute(sql_pm)
+                data_pm = cursor.fetchall()
+                pm_list = [row['pm'] for row in data_pm if 'pm' in row]
+
+
+            return ptime_list, ci_list, so_list, no_list, pm_list
+    except pymysql.err.OperationalError as e:
+        logging.error(f"数据库操作失败: {e}")
+        # 根据具体场景，可以选择返回空列表、抛出异常或返回特定错误码
+        return [], [], [], [], []
+    #except Exception as e:
+        #logging.error(f"未知错误: {e}")
+        # 同上，根据具体场景进行处理
+        #return [], []
+def visualize_data(ptime_list, ci_list, so_list, no_list, pm_list):
+    """
+    可视化数据。
+    :param ptime_list: ptime数据列表
+    :param ci_list: ci数据列表
+    :param column_to_plot: 需要绘制的列名
+    """
+    if not ptime_list or not ci_list or not so_list or not no_list or not pm_list:
+        logging.error("数据为空，无法进行可视化")
+        return
+    #y_list=[]
+    #for i in range(4,8):
+     #   y_list.append(i)
+    plt.figure(figsize=(15,10),dpi=80)
+
+    plt.xlabel('Ptime')
+
+    plt.title('CI over time')
+    plt.plot(ptime_list, ci_list,label='CI')
+    plt.plot(ptime_list, so_list,label='SO2')
+    plt.plot(ptime_list, no_list, label='NO2')
+    plt.plot(ptime_list, pm_list, label='PM2.5')
+    plt.legend()
+    plt.show()
+
+
+
+if __name__ == "__main__":
+    db_config = {
+        "host": '127.0.0.1',
+        "user": "root",
+        "password": 'mysql>hyx123',
+        "db": 'airquility',
+        "charset": 'utf8',
+        "cursorclass": pymysql.cursors.DictCursor
+    }
+
+    ptime_list, ci_list,so_list ,no_list, pm_list= get_data(db_config)
+    visualize_data(ptime_list, ci_list, so_list, no_list, pm_list)
+
+    print(pymysql.__version__)
+
+'''
+    window= Tk()
+    window.title("每日空气质量")
+    window.geometry("300x200")
+#Label(window, text="图表已生成为air_quality_index.html").pack()
+
+    window.mainloop()
+    '''
+

AirQuilitySys/DayAirbing.py

@@ -0,0 +1,154 @@
+import logging
+import pymysql
+import subprocess
+import numpy as np
+from matplotlib import pyplot as plt
+#%matplotlib inline
+from tkinter import Tk
+from pyecharts import options as _opts
+from pyecharts.charts import Bar
+
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+#db_config={'host':'127.0.0.1','user':'root','password':'mysql>hyx123','db':'airquility','charset':'utf8'}
+#ptimelist=[]
+#cilist=[]
+#data_dict=dict(zip(ptimelist,cilist))
+
+jan_list = []
+feb_list = []
+mar_list = []
+apr_list = []
+may_list = []
+ptime_list = []
+
+def get_data(db_config):
+    """
+    从数据库中获取ptime和ci数据。
+    :param db_config: 数据库配置字典
+    :return: 包含ptime和ci的元组列表
+    """
+ # 存储ptime数据的列表
+
+    try:
+        with pymysql.connect(**db_config) as conn:
+            logging.info("数据库连接成功")
+
+            with conn.cursor() as cursor:
+                # 使用单个查询以提高性能
+
+                sql_ptime = "SELECT ptime FROM May"
+                cursor.execute(sql_ptime)
+                data_ptime = cursor.fetchall()
+                ptime_list = [row['ptime'] for row in data_ptime if 'ptime' in row]
+
+                sql_may = "SELECT pm FROM may"
+                cursor.execute(sql_may)
+                data_may = cursor.fetchall()
+                may_list = [row['pm'] for row in data_may if 'pm' in row]
+
+                sql_feb="SELECT pm FROM feb"
+                cursor.execute(sql_feb)
+                data_feb=cursor.fetchall()
+                #print(data_ci)
+                feb_list = [row['pm'] for row in data_feb if 'pm' in row]
+
+                sql_jan = "SELECT pm FROM jan"
+                cursor.execute(sql_jan)
+                data_jan = cursor.fetchall()
+                # print(data_ci)
+                jan_list = [row['pm'] for row in data_jan if 'pm' in row]
+
+                sql_mar = "SELECT pm FROM mar"
+                cursor.execute(sql_mar)
+                data_mar = cursor.fetchall()
+                # print(data_ci)
+                mar_list = [row['pm'] for row in data_mar if 'pm' in row]
+
+                sql_apr = "SELECT pm FROM apr"
+                cursor.execute(sql_apr)
+                data_apr = cursor.fetchall()
+                # print(data_ci)
+                apr_list = [row['pm'] for row in data_apr if 'pm' in row]
+
+            return ptime_list, may_list, feb_list, jan_list, mar_list, apr_list
+    except pymysql.err.OperationalError as e:
+        logging.error(f"数据库操作失败: {e}")
+        # 根据具体场景，可以选择返回空列表、抛出异常或返回特定错误码
+        return [], [], [], [], [], []
+
+def average(str_list):
+    if not str_list:  # 检查列表是否为空
+        return 0  # 或者根据需要处理，比如返回None或者抛出异常
+    num_list = [float(item) for item in str_list]  # 假设可能有浮点数
+    return sum(num_list) / len(num_list)
+
+
+
+def visualize_data(ptime_list, may_list, feb_list, jan_list, mar_list, apr_list):
+    """
+    可视化数据。
+    :param ptime_list: ptime数据列表
+    :param ci_list: ci数据列表
+    :param column_to_plot: 需要绘制的列名
+    """
+    if not may_list or not feb_list or not jan_list:
+        logging.error("数据为空，无法进行可视化")
+        return
+    #y_list=[]
+    #for i in range(4,8):
+     #   y_list.append(i)
+    x = np.arange(26)
+    bar_width = 0.2
+    # 调用函数并打印结果
+    jan_value = average(jan_list)
+    feb_value = average(feb_list)
+    may_value = average(may_list)
+    mar_value = average(mar_list)
+    apr_value = average(apr_list)
+    # 创建图形对象
+    fig = plt.figure("average_pm2.5")
+
+    #plt.title('每月pm2.5平均指数')
+    # 创建子图
+    ax = fig.add_axes([0, 0, 1, 1])
+    # 让饼状图变成圆形
+    ax.axis('equal')
+    # 准备数据
+    #labels = ['jan', 'feb', 'may','mar','apr']
+    #num_data = [jan_value, feb_value, may_value, mar_value, apr_value]
+    plt.figure(figsize=(15, 10), dpi=80)
+    plt.bar(ptime_list, apr_value, tick_label=ptime_list, width=bar_width)
+    plt.bar(x + bar_width, may_value, width=bar_width)
+    # 饼状图之间的间隙大小
+    #explode = (0.02, 0.03, 0.02, 0.01, 0.01)
+    # 画饼
+    #ax.pie(num_data, labels=labels, autopct='%1.1f%%', explode=explode)
+    plt.show()
+
+
+
+if __name__ == "__main__":
+    db_config = {
+        "host": '127.0.0.1',
+        "user": "root",
+        "password": 'mysql>hyx123',
+        "db": 'airquility',
+        "charset": 'utf8',
+        "cursorclass": pymysql.cursors.DictCursor
+    }
+
+    ptime_list, may_list, feb_list, jan_list, mar_list, apr_list= get_data(db_config)
+    visualize_data(ptime_list, may_list, feb_list, jan_list, mar_list, apr_list)
+
+    #print(pymysql.__version__)
+
+'''
+    window= Tk()
+    window.title("每日空气质量")
+    window.geometry("300x200")
+#Label(window, text="图表已生成为air_quality_index.html").pack()
+
+    window.mainloop()
+    '''
+

AirQuilitySys/DayAirzhu.py

@@ -0,0 +1,132 @@
+import logging
+import pymysql
+import subprocess
+import numpy as np
+from matplotlib import pyplot as plt
+from tkinter import Tk
+from pyecharts import options as _opts
+from pyecharts.charts import Bar
+
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+#db_config={'host':'127.0.0.1','user':'root','password':'mysql>hyx123','db':'airquility','charset':'utf8'}
+#ptimelist=[]
+#cilist=[]
+#data_dict=dict(zip(ptimelist,cilist))
+
+def get_data(db_config):
+    """
+    从数据库中获取ptime和ci数据。
+    :param db_config: 数据库配置字典
+    :return: 包含ptime和ci的元组列表
+    """
+    ptime_list = []  # 存储ptime数据的列表
+    ci_list = []  # 存储ci数据的列表
+
+
+    try:
+        with pymysql.connect(**db_config) as conn:
+            logging.info("数据库连接成功")
+            with conn.cursor() as cursor:
+                # 使用单个查询以提高性能
+                sql_ptime = "SELECT ptime FROM May"
+                cursor.execute(sql_ptime)
+                data_ptime = cursor.fetchall()
+                ptime_list = [row['ptime'] for row in data_ptime if 'ptime' in row]
+                #row_list=[val for sublist in row for val in sublist]
+
+                sql_ci="SELECT ci FROM may"
+                cursor.execute(sql_ci)
+                data_ci=cursor.fetchall()
+                #print(data_ci)
+                ci_list = [row['ci'] for row in data_ci if 'ci' in row]
+
+                sql_so = "SELECT so FROM may"
+                cursor.execute(sql_so)
+                data_so = cursor.fetchall()
+                so_list = [row['so'] for row in data_so if 'so' in row]
+
+                sql_no = "SELECT no FROM may"
+                cursor.execute(sql_no)
+                data_no = cursor.fetchall()
+                no_list = [row['no'] for row in data_no if 'no' in row]
+
+                sql_pm = "SELECT pm FROM may"
+                cursor.execute(sql_pm)
+                data_pm = cursor.fetchall()
+                pm_list = [row['pm'] for row in data_pm if 'pm' in row]
+
+
+            return ptime_list, ci_list, so_list, no_list, pm_list
+    except pymysql.err.OperationalError as e:
+        logging.error(f"数据库操作失败: {e}")
+        # 根据具体场景，可以选择返回空列表、抛出异常或返回特定错误码
+        return [], [], [], [], []
+    #except Exception as e:
+        #logging.error(f"未知错误: {e}")
+        # 同上，根据具体场景进行处理
+        #return [], []
+def visualize_data(ptime_list, ci_list, so_list, no_list, pm_list):
+    """
+    可视化数据。
+    :param ptime_list: ptime数据列表
+    :param ci_list: ci数据列表
+    :param column_to_plot: 需要绘制的列名
+    """
+    if not ptime_list or not ci_list or not so_list or not no_list or not pm_list:
+        logging.error("数据为空，无法进行可视化")
+        return
+    #y_list=[]
+    #for i in range(4,8):
+     #   y_list.append(i)
+    plt.figure(figsize=(15,10),dpi=80)
+    x = np.arange(26)
+    bar_width = 0.2
+    """
+    plt.bar(ptime_list,  # 柱状图柱体标签值
+            ci_list,  # 柱体高度
+            align='center',  # 柱体对齐方式
+            color='red',  # 柱体颜色
+            tick_label=ptime_list,  # 刻度标签值
+            hatch='/')  # 填充样式，越密集填充就越密
+    plt.bar(ptime_list,  # 柱状图柱体标签值
+            so_list,  # 柱体高度
+            align='center',  # 柱体对齐方式
+            color='blue',  # 柱体颜色
+            tick_label=ptime_list,  # 刻度标签值
+            hatch='/')  # 填充样式，越密集填充就越密
+        """
+    plt.xlabel('Ptime')
+    plt.bar(ptime_list, ci_list, tick_label=ptime_list, width=bar_width)
+    plt.bar(x + bar_width, so_list, width=bar_width)
+    #plt.bar(x + bar_width, no_list, width=bar_width)
+    #plt.bar(x + bar_width, pm_list, width=bar_width)
+    plt.title('CI over time')
+    plt.show()
+
+
+
+if __name__ == "__main__":
+    db_config = {
+        "host": '127.0.0.1',
+        "user": "root",
+        "password": 'mysql>hyx123',
+        "db": 'airquility',
+        "charset": 'utf8',
+        "cursorclass": pymysql.cursors.DictCursor
+    }
+
+    ptime_list, ci_list, so_list, no_list, pm_list = get_data(db_config)
+    visualize_data(ptime_list, ci_list, so_list, no_list, pm_list)
+
+    print(pymysql.__version__)
+
+'''
+    window= Tk()
+    window.title("每日空气质量")
+    window.geometry("300x200")
+#Label(window, text="图表已生成为air_quality_index.html").pack()
+
+    window.mainloop()
+    '''
+

AirQuilitySys/LSTM_airqui.py

@@ -0,0 +1,63 @@
+import keras
+import matplotlib.pyplot as plt
+import pandas as pd
+import tensorflow as tf
+import numpy as np
+from sklearn.preprocessing import MinMaxScaler
+from keras.layers import Dense, LSTM, Activation, Dropout
+from keras.optimizers import SGD
+
+colum = 13
+step = 50
+df = pd.read_csv('文件名')
+df_for_training=df[:24000]
+df_for_testing=df[24000:]
+# print(df_for_testing.iloc[:, 2:])
+
+scaler = MinMaxScaler(feature_range=(-1, 1))
+df_for_training_scaled = scaler.fit_transform(df_for_training.iloc[:, 2:])
+print("df_for_training_scaled shape:",df_for_training_scaled.shape)
+#print(df_for_training_scaled.shape)
+#print(df_for_testing_scaled.shape)
+
+#抽取特征与标签列
+def createXY(dataset, n_past):
+    dataX = []
+    dataY = []
+    for i in range(n_past, len(dataset)):
+        dataX.append(dataset[i - n_past:i, 1:dataset.shape[1]])
+        dataY.append(dataset[i, 0])
+    return np.array(dataX), np.array(dataY)
+#trainX,testX数据的shape为[samples, steps, features]
+trainX, trainY = createXY(df_for_training_scaled, step)
+testX, testY = createXY(df_for_testing_scaled, step)
+
+#构建模型
+def build_model():
+    model = tf.keras.models.Sequential()
+    #经试验，如果下一层还是LSTM的话必须将return_sequences设置为True
+    model.add(LSTM(20, input_shape=(step, column), return_sequences=True))
+    model.add(LSTM(20))
+    model.add(Activation('relu'))
+    model.add(Dropout(0.2))
+    model.add(Dense(1))
+    model.compile(loss='mae', optimizer=SGD(lr=0.1,momentum=0.3))
+    return model
+
+lstm_net = build_model()
+lstm_net.fit(trainX, trainY, batch_size=8, epochs=100)
+predictions = lstm_net.predict(testX)
+
+#进行逆变换
+test_Predict_copy = np.repeat(predictions,column+1,axis=-1)
+test_Predict_inverse = scaler.inverse_transform(test_Predict_copy)[:,0]
+#test_Predict_inverse = scaler.inverse_transform(test_Predict)
+test_label = np.array(df_for_testing['omega_vsg_1'])[50:]
+testY_copy = np.repeat(np.reshape(testY,(len(testY), 1)),column+1,axis=-1)
+
+testY_inverse = scaler = scaler.inverse_transform(testY_copy)[:,0]
+
+plt.plot(test_Predict_inverse,color='red')
+plt.plot(test_label,color='green')
+plt.plot(testY_inverse, color='blue')
+plt.savefig('result_test.png')

AirQuilitySys/Login.py

@@ -0,0 +1,60 @@
+from tkinter import *
+import subprocess
+import sys
+from tkinter import messagebox
+user_login={'aaa':'123456','bbb':'888888','ccc':'333333'}
+count=0
+
+def run_AirQui():
+    """函数用于执行另一个Python脚本"""
+    try:
+        #subprocess.run(["python", "AirQui.py"], check=True)  # 尝试运行另一个Python脚本
+        #sys.exit()
+        subprocess.run(["D:\Pycharm\Project\AirQuilitySys\.venv\Scripts\python.exe", "AirQui.py"], check=True)
+        sys.exit(0)
+    except subprocess.CalledProcessError as e:
+        print(f"执行脚本时发生错误: {e}")
+def login():
+    global count
+    username=entry_username.get()
+    if username not in user_login:
+        label_message.config(text='账号错误！')
+    else:
+        password=entry_password.get()
+        if(password==user_login[username]):
+            label_message.config(text='登录成功！')
+            run_AirQui()
+
+        else:
+            label_message.config(text='密码错误！还可以尝试{}次'.format(2-count))
+            count=count+1
+            if count == 3:
+                label_message.config(text='登录失败！')
+                button.config(state="disabled")
+# 创建主窗口
+window=Tk()
+window.title("用户登录")
+window.geometry("300x200")
+
+label_username=Label(window,text="账号：")
+label_username.pack()
+
+entry_username=Entry(window)
+entry_username.pack()
+
+label_password=Label(window,text="密码：")
+label_password.pack()
+
+entry_password=Entry(window,show='*')
+entry_password.pack()
+
+# 创建一个按钮，点击时调用run_another_program函数
+button = Button(window, text="登录", command=login)
+button.pack()  # 设置按钮布局
+
+label_message=Label(window,text="")
+label_message.pack()
+
+window.mainloop()
+# 运行Tkinter事件循环
+

AirQuilitySys/data.py

@@ -0,0 +1,7 @@
+import requests
+res = requests.get('http://www.daqi110.com/content/environment/index.html')
+print(res)
+print(type(res))
+#>>>
+#<Response [200]>
+#<class 'requests.models.Response'>

AirQuilitySys/test.py

@@ -0,0 +1 @@
+import matplotlib.pyplot as plt

AirQuilitySys/time.py

@@ -0,0 +1,382 @@
+import os
+import pandas as pd
+import numpy as np
+from sqlalchemy import create_engine, text
+from sklearn.preprocessing import MinMaxScaler
+import logging
+from sklearn.model_selection import train_test_split
+from keras.callbacks import EarlyStopping, ModelCheckpoint
+from sklearn.metrics import mean_squared_error
+from keras.models import Sequential
+from keras.layers import LSTM, Dense
+from tensorflow.keras.layers import Input
+from keras.preprocessing.sequence import pad_sequences
+import tensorflow as tf
+from tensorflow.keras.models import Sequential
+from tensorflow.keras.layers import LSTM, Dense
+from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint
+from tensorflow.keras.models import Model  # 导入Model类
+import matplotlib.pyplot as plt
+import joblib
+import pymysql
+import logging
+from datetime import datetime
+
+logging.basicConfig(level=logging.ERROR, format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
+def get_db_config():
+    #从环境变量中获取数据库配置。
+    config = {
+        "host": os.getenv('DB_HOST', '127.0.0.1'),
+        "user": os.getenv('DB_USER', 'root'),
+        "password": os.getenv('DB_PASSWORD','mysql>hyx123'),
+        "db": os.getenv('DB_NAME', 'airquility'),
+        "charset": 'utf8',
+    }
+
+    # 检查环境变量是否已设置
+    for key, value in config.items():
+        if value is None:
+            raise ValueError(f"缺少环境变量: {key}")
+
+    return config
+
+
+def create_database_engine(config):
+    """
+    创建数据库引擎。
+    """
+    db_string = f'mysql+pymysql://{config["user"]}:{config["password"]}@{config["host"]}/{config["db"]}?charset={config["charset"]}'
+
+    try:
+        engine = create_engine(db_string)
+        print(type(engine))
+    except Exception as e:
+        print(f"创建数据库引擎失败: {e}")
+        # 根据需要处理异常，例如记录日志或重试
+        raise  # 如果需要将异常继续抛出
+    return engine
+
+
+def fetch_data(engine, query):
+    """
+    从数据库中获取数据。
+    参数:
+        engine: 数据库连接引擎对象。
+        query: SQL查询字符串。
+    返回:
+        查询结果的数据框(df)。
+    """
+    # 确保query是字符串类型
+    if not isinstance(query, str):
+        logging.error("查询字符串类型错误，query应为字符串。")
+        raise ValueError("查询字符串类型错误，query应为字符串。")
+
+    if not query.strip():
+        logging.error("查询字符串为空。")
+        raise ValueError("查询字符串为空。")
+
+    try:
+        df = pd.read_sql(text(query), engine)
+        return df
+    except Exception as e:
+        logging.error(f"执行SQL查询失败: {e}")
+        raise  # 重新抛出异常以便上层处理
+
+def preprocess_data(df, target_col, default_year=2024, features=None):
+    """
+    对数据进行预处理，包括日期列转换、特征标准化等。
+    """
+    # 检查df是否为空
+    if df.empty:
+        logging.error("输入的DataFrame为空")
+        return None, None, None
+
+    # 检查'ptime'列是否存在
+    if 'ptime' not in df.columns:
+        logging.error("DataFrame中不存在'ptime'列")
+        return None, None, None
+    default_year = 2024
+    df['ptime'] = df['ptime'].apply(lambda x: datetime.strptime(f"{default_year}/{x}", "%Y/%m/%d"))
+    # 或者，如果使用pd.to_datetime，并且'ptime'格式特殊，需要指定格式
+    # df['ptime'] = pd.to_datetime(df['ptime'], errors='coerce', format='%m/%d').dt.strftime('%Y-%m-%d')
+
+    print(df.head)
+
+    # 如果'ptime'已经是datetime类型，则无需转换
+    if df['ptime'].dtype == 'datetime64[ns]':
+        print("ptime列已经是以日期时间格式存储。")
+    else:
+        try:
+            # 尝试将'ptime'列转换为datetime类型
+            df['ptime'] = pd.to_datetime(df['ptime'], format='%m/%d/%Y')
+        except ValueError:
+            logging.error("ptime列转换为datetime类型失败，可能是因为格式不正确。")
+            return None, None, None
+
+    # 设置'ptime'为索引
+    #df.set_index('ptime', inplace=True)
+
+    # 确定features列表
+    if target_col in df.columns:
+        features = df.columns.drop(target_col)
+        print("features:", features)
+    else:
+        logging.warning(f"目标列 '{target_col}' 在DataFrame中未找到，将不进行列删除操作。")
+        features = df.columns
+
+    # 检查features是否被正确设置
+    if features is None:
+        logging.error("未找到任何特征列。")
+        return None, None, None
+
+    print("@@@@")
+    print(target_col)
+    print("@@@@")
+    try:
+        df.set_index('ptime', inplace=True)
+    except KeyError:
+        print("列 'ptime' 不存在，无法设置为索引。")
+        # 在这里处理缺少'ptime'的情况，比如跳过相关操作或使用其他列
+    # 使用MinMaxScaler进行特征缩放
+    scaler = MinMaxScaler()
+    scaled_features = scaler.fit_transform(df[features])
+    scaled_target = scaler.fit_transform(df.index.values.reshape(-1, 1))
+    print("~~~")
+    return scaled_features, scaled_target, scaler
+
+
+def split_dataset_into_train_test(features, target, test_size=0.2):
+    """
+    切分数据集为训练集和测试集。
+    """
+    # 检查features和target的类型以及长度是否相等
+    if not isinstance(features, np.ndarray) or not isinstance(target, np.ndarray):
+        raise TypeError("features and target must be numpy arrays")
+    if len(features) != len(target):
+        raise ValueError("features and target must have the same length")
+
+    # 检查test_size是否在合理的范围内
+    if not 0 < test_size < 1:
+        raise ValueError("test_size must be between 0 and 1")
+
+    # 计算训练集大小
+    train_size = int(len(features) * (1 - test_size))
+
+    # 使用numpy的切片操作，这不会创建新的数据副本，提高性能
+    train_features, test_features = features[:train_size], features[train_size:]
+    train_target, test_target = target[:train_size], target[train_size:]
+    print("123456")
+    print(features)
+    print(target)
+    print(train_features)
+    print(train_target)
+    print(test_features)
+    print(test_target)
+    return train_features, test_features, train_target, test_target
+
+
+def validate_data_shapes(train_features, test_features, n_steps):
+    """
+    验证训练和测试数据形状是否符合预期。
+    """
+    if train_features.shape[1] != n_steps or test_features.shape[1] != n_steps:
+        raise ValueError(f"训练和测试特征的第二维度（时间步长）应为{n_steps}")
+    print("7890")
+
+
+def build_model(n_steps, lstm_units, dense_units, input_shape):
+    inputs = Input(shape=input_shape)  # 添加Input对象
+    x = LSTM(lstm_units)(inputs)  # 直接将Input对象传递给LSTM层
+    outputs = Dense(dense_units)(x)
+    model = tf.keras.Model(inputs=inputs, outputs=outputs)
+    model.compile(optimizer='adam', loss='mse')
+    print("!!!")
+    return model
+
+
+def validate_params(epochs, batch_size):
+    """
+    确保 epochs 和 batch_size 是合法的参数。
+    """
+    if not isinstance(epochs, int) or epochs <= 0:
+        raise ValueError("epochs 应该是一个正整数")
+    if not isinstance(batch_size, int) or batch_size <= 0:
+        raise ValueError("batch_size 应该是一个正整数")
+    if epochs <= 0 or batch_size <= 0:
+        raise ValueError("epochs和batch_size必须大于0")
+    print("%%%")
+
+
+def ensure_directory_safety(path:str):
+    """
+    确保路径安全且存在。
+    """
+    if not os.path.isabs(path):
+        raise ValueError("路径应该是绝对路径")
+    directory = os.path.dirname(path)
+    print(directory)
+
+    try:
+        # 检查目录是否需要创建
+        if not os.path.exists(directory):
+            # 添加日志记录
+            logger.info(f"目录 {directory} 不存在，开始创建。")
+            # 使用 exist_ok=True 避免在目录已存在时抛出异常
+            os.makedirs(directory, exist_ok=True)
+            logger.info(f"目录 {directory} 创建成功。")
+    except PermissionError:
+        # 捕获权限异常，给出清晰的错误提示
+        logger.error(f"没有权限在 {directory} 创建目录。")
+        raise
+    except Exception as e:
+        # 捕获其他异常，记录并抛出
+        logger.error(f"创建目录 {directory} 时发生未知错误：{e}")
+        raise
+    print("===")
+def train_model(model: Model, train_features, train_target, test_features, test_target, epochs: int, batch_size: int,
+                patience: int, save_best_only: bool = True, monitor: str = 'val_loss', mode: str = 'min',
+                model_path: str = "best_model.h5") -> dict:
+    """
+    训练模型，并根据早停策略和性能指标保存最佳模型。
+
+    :param model: Keras模型实例
+    :param train_features: 训练特征
+    :param train_target: 训练目标
+    :param test_features: 测试特征
+    :param test_target: 测试目标
+    :param epochs: 训练轮数
+    :param batch_size: 批量大小
+    :param patience: 早停策略的耐心值
+    :param save_best_only: 是否只保存最佳模型
+    :param monitor: 监控的指标
+    :param mode: 监控指标的模式（min/max）
+    :param model_path: 模型保存路径
+    :return: 训练历史记录
+    """
+    logging.basicConfig(level=logging.INFO)
+
+    model_path = "/path/to/your/model.h5"
+    validate_params(epochs, batch_size)
+    ensure_directory_safety(model_path)
+
+    # 使用ModelCheckpoint保存最佳模型
+    filepath = model_path
+    checkpoint = ModelCheckpoint(filepath, monitor=monitor, verbose=1, save_best_only=save_best_only, mode=mode)
+
+    # 定义早停策略
+    early_stopping = EarlyStopping(monitor=monitor, patience=patience, verbose=1)
+
+    try:
+        history = model.fit(train_features, train_target, epochs=epochs, batch_size=batch_size,
+                            validation_data=(test_features, test_target), verbose=1,
+                            callbacks=[early_stopping, checkpoint])
+        logging.info("###")
+        return history
+    except ValueError as ve:
+        logging.error(f"参数错误: {ve}")
+        raise
+    except OSError as oe:
+        logging.error(f"文件操作错误: {oe}")
+        raise
+    except Exception as e:
+        logging.error(f"模型训练过程中发生异常: {e}")
+        raise
+
+def build_and_train_model(n_steps, features, target, train_features, train_target, test_features, test_target,lstm_units=50, dense_units=1, optimizer='adam', loss='mse', epochs=100, batch_size=32,patience=10, model_save_path='model.h5'):
+    """
+    构建LSTM模型并进行训练，增加了参数可配置性，早停策略和模型保存。
+    """
+    # 输入数据验证
+    if not (isinstance(train_features, np.ndarray) and isinstance(train_target, np.ndarray) and isinstance(test_features, np.ndarray) and isinstance(test_target, np.ndarray)):
+        raise ValueError("输入数据train_features, train_target, test_features, test_target必须是numpy数组")
+
+    checkpoint = ModelCheckpoint(filepath="/path/to/your/model.keras",  # 注意这里的路径保持为.h5
+                                 monitor='val_loss',  # 或您希望监控的指标
+                                 verbose=1,
+                                 save_best_only=True,
+                                 mode='min')
+
+    # 数据形状验证
+    validate_data_shapes(train_features, test_features, n_steps)
+
+    model = build_model(n_steps, lstm_units, dense_units, input_shape)
+
+    # 早停策略
+    early_stopping = EarlyStopping(monitor='val_loss', patience=patience, verbose=1)
+
+    history = model.fit(train_features, train_target,
+                        validation_data=(test_features, test_target),
+                        epochs=epochs,
+                        batch_size=batch_size,
+                        callbacks=[checkpoint],
+                        # 其他参数...
+                        )    # 模型保存
+    # 增加了路径验证来防止潜在的安全问题，这里简化处理，实际应用中可能需要更复杂的逻辑
+    if not model_save_path.endswith('.h5'):
+        model_save_path += '.h5'
+    model.save(model_save_path)
+
+    return model, history
+
+
+def evaluate_model(model, scaler, test_target, predictions):
+    """
+    评估模型性能并反向转换预测结果。
+    """
+    predictions = scaler.inverse_transform(predictions)
+    test_target_inv = scaler.inverse_transform(test_target.reshape(-1, 1))
+    mse = mean_squared_error(test_target_inv, predictions)
+    print(f'Mean Squared Error: {mse}')
+
+    return mse
+
+
+if __name__ == "__main__":
+
+    engine = create_database_engine(get_db_config())
+    query = "SELECT ptime, ci FROM may"
+    df = fetch_data(engine, query)
+    target_col = 'ptime'
+    features, target, scaler = preprocess_data(df, target_col)
+
+    train_features, test_features, train_target, test_target = split_dataset_into_train_test(features, target, test_size=0.2)
+
+    n_steps = 5
+    # 假设train_features和test_features是你的数据，且它们是二维数组
+    # 首先，你需要获取或设定一个maxlen，这里假设我们已知或计算出它应该是5
+    maxlen = 5
+
+    # 对训练数据进行填充或截断
+    train_features_padded = pad_sequences(train_features, maxlen=maxlen, padding='post', truncating='post')
+
+    # 对测试数据进行同样的处理
+    test_features_padded = pad_sequences(test_features, maxlen=maxlen, padding='post', truncating='post')
+
+    input_shape = (n_steps, int(train_features.shape[1]))
+
+
+    model, history = build_and_train_model(n_steps=n_steps,
+                                           features=features,
+                                           target=target,
+                                           train_target=train_target,
+                                           test_target=test_target,
+                                           train_features=train_features_padded,
+                                           test_features=test_features_padded)
+
+    predictions = model.predict(test_features)
+    mse = evaluate_model(model, scaler, test_target, predictions)
+    # 可视化预测结果（可选）
+
+    #plt.plot(test_target, label='Actual')
+    plt.plot(predictions, label='Predicted')
+    plt.legend()
+    plt.xlabel('Ptime')
+    plt.ylabel('CI')
+    #plt.plot(ptime, ci)
+    plt.show()
+
+    # 保存模型
+    model.save('trained_model.h5')
+    joblib.dump(scaler, 'scaler.joblib')

AirQuilitySys/user.py

@@ -0,0 +1,44 @@
+import mysql.connector
+from mysql.connector import Error
+    def insert_user():
+        try:
+            # 连接到数据库
+            connection = mysql.connector.connect(
+                host='127.0.0.1',
+                user='root',
+                password='mysql>hyx123',
+                database='airquility'
+            )
+
+            if connection.is_connected():
+                db_info = connection.get_server_info()
+                print(f"Connected to MySQL Server version {db_info}")
+
+                cursor = connection.cursor()
+
+                # 从用户接收输入
+                user = input("Enter user: ")
+                password = input("Enter password: ")
+
+                # 准备插入数据的SQL语句
+                sql_insert_query = """INSERT INTO users (user,password) 
+                              VALUES (%s, %s)"""
+
+                # 用户输入的数据作为元组
+                insert_data = (user, password)
+
+                # 执行插入操作
+                cursor.execute(sql_insert_query, insert_data)
+                connection.commit()
+                print("Record inserted successfully into users table.")
+
+        except Error as e:
+            print(f"Error while connecting to MySQL: {e}")
+        finally:
+            if (connection.is_connected()):
+                cursor.close()
+                connection.close()
+                print("MySQL connection is closed")
+
+ # 调用函数插入数据
+insert_user()

airquility/apr.sql

@@ -0,0 +1,70 @@
+/*
+ Navicat Premium Data Transfer
+
+ Source Server         : AirQui
+ Source Server Type    : MySQL
+ Source Server Version : 80026
+ Source Host           : localhost:3306
+ Source Schema         : airquility
+
+ Target Server Type    : MySQL
+ Target Server Version : 80026
+ File Encoding         : 65001
+
+ Date: 03/06/2024 18:37:46
+*/
+
+SET NAMES utf8mb4;
+SET FOREIGN_KEY_CHECKS = 0;
+
+-- ----------------------------
+-- Table structure for apr
+-- ----------------------------
+DROP TABLE IF EXISTS `apr`;
+CREATE TABLE `apr`  (
+  `ci` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `city` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `co` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `no2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `o3` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm10` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm2.5` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `ptime` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `so2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL
+) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
+
+-- ----------------------------
+-- Records of apr
+-- ----------------------------
+INSERT INTO `apr` VALUES ('5.11', '株洲', '1.4', '36', '88', '89', '67', '1706284800000', '8');
+INSERT INTO `apr` VALUES ('5.13', '株洲', '1.4', '37', '88', '89', '67', '1706371200000', '8');
+INSERT INTO `apr` VALUES ('5.17', '株洲', '1.4', '37', '87', '90', '68', '1706457600000', '8');
+INSERT INTO `apr` VALUES ('5.11', '株洲', '1.4', '37', '87', '88', '67', '1706544000000', '8');
+INSERT INTO `apr` VALUES ('5.07', '株洲', '1.4', '37', '87', '87', '66', '1706630400000', '8');
+INSERT INTO `apr` VALUES ('4.95', '株洲', '1.3', '36', '87', '85', '65', '1706716800000', '7');
+INSERT INTO `apr` VALUES ('4.9', '株洲', '1.3', '36', '86', '83', '64', '1706803200000', '7');
+INSERT INTO `apr` VALUES ('4.8', '株洲', '1.3', '35', '86', '82', '62', '1706889600000', '7');
+INSERT INTO `apr` VALUES ('4.79', '株洲', '1.3', '35', '86', '81', '62', '1706976000000', '7');
+INSERT INTO `apr` VALUES ('4.71', '株洲', '1.3', '34', '86', '80', '61', '1707062400000', '7');
+INSERT INTO `apr` VALUES ('4.66', '株洲', '1.3', '34', '85', '79', '60', '1707148800000', '7');
+INSERT INTO `apr` VALUES ('4.69', '株洲', '1.3', '34', '85', '79', '61', '1707235200000', '7');
+INSERT INTO `apr` VALUES ('4.7', '株洲', '1.3', '33', '87', '79', '62', '1707321600000', '7');
+INSERT INTO `apr` VALUES ('4.82', '株洲', '1.3', '33', '90', '82', '64', '1707408000000', '7');
+INSERT INTO `apr` VALUES ('5', '株洲', '1.3', '33', '89', '87', '68', '1707494400000', '7');
+INSERT INTO `apr` VALUES ('5.07', '株洲', '1.3', '32', '94', '88', '69', '1707580800000', '8');
+INSERT INTO `apr` VALUES ('5.06', '株洲', '1.3', '32', '93', '88', '69', '1707667200000', '8');
+INSERT INTO `apr` VALUES ('4.99', '株洲', '1.3', '31', '92', '87', '68', '1707753600000', '8');
+INSERT INTO `apr` VALUES ('4.99', '株洲', '1.3', '31', '92', '87', '68', '1707840000000', '8');
+INSERT INTO `apr` VALUES ('4.95', '株洲', '1.3', '31', '92', '86', '67', '1707926400000', '8');
+INSERT INTO `apr` VALUES ('4.86', '株洲', '1.3', '30', '91', '85', '66', '1708012800000', '7');
+INSERT INTO `apr` VALUES ('4.84', '株洲', '1.3', '30', '90', '84', '66', '1708099200000', '7');
+INSERT INTO `apr` VALUES ('4.77', '株洲', '1.3', '29', '90', '83', '65', '1708185600000', '7');
+INSERT INTO `apr` VALUES ('4.74', '株洲', '1.3', '29', '90', '83', '64', '1708272000000', '7');
+INSERT INTO `apr` VALUES ('4.69', '株洲', '1.3', '29', '89', '82', '63', '1708358400000', '7');
+INSERT INTO `apr` VALUES ('4.63', '株洲', '1.3', '28', '89', '81', '62', '1708444800000', '7');
+INSERT INTO `apr` VALUES ('4.61', '株洲', '1.3', '28', '89', '80', '62', '1708531200000', '7');
+INSERT INTO `apr` VALUES ('4.57', '株洲', '1.3', '28', '89', '79', '61', '1708617600000', '7');
+INSERT INTO `apr` VALUES ('4.55', '株洲', '1.3', '27', '89', '79', '61', '1708704000000', '7');
+INSERT INTO `apr` VALUES ('4.52', '株洲', '1.3', '27', '88', '78', '61', '1708790400000', '7');
+
+SET FOREIGN_KEY_CHECKS = 1;

airquility/feb.sql

@@ -0,0 +1,69 @@
+/*
+ Navicat Premium Data Transfer
+
+ Source Server         : AirQui
+ Source Server Type    : MySQL
+ Source Server Version : 80026
+ Source Host           : localhost:3306
+ Source Schema         : airquility
+
+ Target Server Type    : MySQL
+ Target Server Version : 80026
+ File Encoding         : 65001
+
+ Date: 03/06/2024 18:37:36
+*/
+
+SET NAMES utf8mb4;
+SET FOREIGN_KEY_CHECKS = 0;
+
+-- ----------------------------
+-- Table structure for feb
+-- ----------------------------
+DROP TABLE IF EXISTS `feb`;
+CREATE TABLE `feb`  (
+  `ci` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `city` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `co` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `no2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `o3` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm10` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm2.5` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `ptime` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `so2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL
+) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
+
+-- ----------------------------
+-- Records of feb
+-- ----------------------------
+INSERT INTO `feb` VALUES ('4.36', '株洲', '1.3', '27', '101', '73', '55', '1711555200000', '7');
+INSERT INTO `feb` VALUES ('4.33', '株洲', '1.3', '27', '102', '72', '54', '1711641600000', '7');
+INSERT INTO `feb` VALUES ('4.3', '株洲', '1.3', '26', '102', '72', '54', '1711728000000', '7');
+INSERT INTO `feb` VALUES ('4.33', '株洲', '1.3', '26', '107', '72', '54', '1711814400000', '7');
+INSERT INTO `feb` VALUES ('4.27', '株洲', '1.3', '26', '106', '71', '53', '1711900800000', '7');
+INSERT INTO `feb` VALUES ('4.3', '株洲', '1.3', '26', '111', '71', '53', '1711987200000', '7');
+INSERT INTO `feb` VALUES ('4.29', '株洲', '1.3', '26', '110', '70', '53', '1712073600000', '7');
+INSERT INTO `feb` VALUES ('4.29', '株洲', '1.3', '26', '110', '70', '53', '1712160000000', '7');
+INSERT INTO `feb` VALUES ('4.29', '株洲', '1.3', '26', '110', '70', '53', '1712246400000', '7');
+INSERT INTO `feb` VALUES ('4.28', '株洲', '1.3', '26', '109', '70', '53', '1712332800000', '7');
+INSERT INTO `feb` VALUES ('4.28', '株洲', '1.3', '26', '108', '70', '53', '1712419200000', '7');
+INSERT INTO `feb` VALUES ('4.3', '株洲', '1.3', '26', '112', '70', '53', '1712505600000', '7');
+INSERT INTO `feb` VALUES ('4.29', '株洲', '1.3', '26', '112', '69', '53', '1712592000000', '7');
+INSERT INTO `feb` VALUES ('4.29', '株洲', '1.3', '26', '112', '69', '53', '1712678400000', '7');
+INSERT INTO `feb` VALUES ('4.27', '株洲', '1.3', '26', '112', '69', '52', '1712764800000', '7');
+INSERT INTO `feb` VALUES ('4.26', '株洲', '1.3', '26', '111', '69', '52', '1712851200000', '7');
+INSERT INTO `feb` VALUES ('4.26', '株洲', '1.3', '26', '110', '69', '52', '1712937600000', '7');
+INSERT INTO `feb` VALUES ('4.24', '株洲', '1.3', '26', '110', '68', '52', '1713024000000', '7');
+INSERT INTO `feb` VALUES ('4.25', '株洲', '1.3', '26', '112', '68', '52', '1713110400000', '7');
+INSERT INTO `feb` VALUES ('4.22', '株洲', '1.3', '25', '112', '68', '52', '1713196800000', '7');
+INSERT INTO `feb` VALUES ('4.22', '株洲', '1.3', '25', '112', '68', '52', '1713283200000', '7');
+INSERT INTO `feb` VALUES ('4.19', '株洲', '1.3', '25', '112', '68', '51', '1713369600000', '7');
+INSERT INTO `feb` VALUES ('4.18', '株洲', '1.3', '25', '112', '67', '51', '1713456000000', '7');
+INSERT INTO `feb` VALUES ('4.16', '株洲', '1.2', '25', '112', '67', '51', '1713542400000', '7');
+INSERT INTO `feb` VALUES ('4.16', '株洲', '1.2', '25', '112', '67', '51', '1713628800000', '7');
+INSERT INTO `feb` VALUES ('4.13', '株洲', '1.2', '25', '111', '66', '51', '1713715200000', '7');
+INSERT INTO `feb` VALUES ('4.12', '株洲', '1.2', '25', '113', '66', '50', '1713801600000', '7');
+INSERT INTO `feb` VALUES ('4.12', '株洲', '1.2', '25', '113', '66', '50', '1713888000000', '7');
+INSERT INTO `feb` VALUES ('4.12', '株洲', '1.2', '25', '113', '66', '50', '1713974400000', '7');
+
+SET FOREIGN_KEY_CHECKS = 1;

airquility/jan.sql

@@ -0,0 +1,71 @@
+/*
+ Navicat Premium Data Transfer
+
+ Source Server         : AirQui
+ Source Server Type    : MySQL
+ Source Server Version : 80026
+ Source Host           : localhost:3306
+ Source Schema         : airquility
+
+ Target Server Type    : MySQL
+ Target Server Version : 80026
+ File Encoding         : 65001
+
+ Date: 03/06/2024 18:36:59
+*/
+
+SET NAMES utf8mb4;
+SET FOREIGN_KEY_CHECKS = 0;
+
+-- ----------------------------
+-- Table structure for jan
+-- ----------------------------
+DROP TABLE IF EXISTS `jan`;
+CREATE TABLE `jan`  (
+  `ci` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `city` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `co` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `no2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `o3` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm10` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm2.5` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `ptime` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `so2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL
+) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
+
+-- ----------------------------
+-- Records of jan
+-- ----------------------------
+INSERT INTO `jan` VALUES ('4.13,', '株洲', '1.2', '25', '115', '66', '50', '1714060800000', '7');
+INSERT INTO `jan` VALUES ('4.12', '株洲', '1.2', '25', '114', '66', '50', '1714147200000', '7');
+INSERT INTO `jan` VALUES ('4.14', '株洲', '1.2', '25', '119', '65', '50', '1714233600000', '7');
+INSERT INTO `jan` VALUES ('4.14', '株洲', '1.2', '25', '119', '65', '50', '1714320000000', '7');
+INSERT INTO `jan` VALUES ('4.11', '株洲', '1.2', '25', '118', '65', '49', '1714406400000', '7');
+INSERT INTO `jan` VALUES ('4.09', '株洲', '1.2', '24', '118', '65', '49', '1714492800000', '7');
+INSERT INTO `jan` VALUES ('4.06', '株洲', '1.2', '24', '117', '64', '49', '1714579200000', '7');
+INSERT INTO `jan` VALUES ('4.05', '株洲', '1.2', '24', '116', '64', '49', '1714665600000', '7');
+INSERT INTO `jan` VALUES ('4.05', '株洲', '1.2', '24', '116', '64', '49', '1714752000000', '7');
+INSERT INTO `jan` VALUES ('4.04', '株洲', '1.2', '24', '116', '63', '49', '1714838400000', '7');
+INSERT INTO `jan` VALUES ('4.01', '株洲', '1.2', '24', '115', '63', '48', '1714924800000', '7');
+INSERT INTO `jan` VALUES ('4', '株洲', '1.2', '24', '114', '63', '48', '1715011200000', '7');
+INSERT INTO `jan` VALUES ('4.03', '株洲', '1.2', '24', '119', '63', '48', '1715097600000', '7');
+INSERT INTO `jan` VALUES ('4.0', '株洲', '1.2', '24', '124', '63', '48', '1715184000000', '7');
+INSERT INTO `jan` VALUES ('4.07', '株洲', '1.2', '24', '124', '63', '48', '1715270400000', '7');
+INSERT INTO `jan` VALUES ('4.06', '株洲', '1.2', '24', '123', '63', '48', '1715356800000', '7');
+INSERT INTO `jan` VALUES ('4.07', '株洲', '1.2', '24', '125', '63', '48', '1715443200000', '7');
+INSERT INTO `jan` VALUES ('4.09', '株洲', '1.2', '24', '126', '64', '48', '1715529600000', '7');
+INSERT INTO `jan` VALUES ('4.09', '株洲', '1.2', '24', '126', '64', '48', '1715616000000', '7');
+INSERT INTO `jan` VALUES ('4.09', '株洲', '1.2', '24', '127', '64', '48', '1715702400000', '7');
+INSERT INTO `jan` VALUES ('4.11', '株洲', '1.2', '24', '130', '64', '48', '1715788800000', '7');
+INSERT INTO `jan` VALUES ('4.12', '株洲', '1.2', '24', '132', '64', '48', '1715875200000', '7');
+INSERT INTO `jan` VALUES ('4.1', '株洲', '1.2', '24', '133', '64', '47', '1715961600000', '7');
+INSERT INTO `jan` VALUES ('4.09', '株洲', '1.2', '24', '132', '64', '47', '1716048000000', '7');
+INSERT INTO `jan` VALUES ('4.09', '株洲', '1.2', '24', '132', '64', '47', '1716134400000', '7');
+INSERT INTO `jan` VALUES ('4.09', '株洲', '1.2', '24', '132', '64', '47', '1716220800000', '7');
+INSERT INTO `jan` VALUES ('4.06', '株洲', '1.2', '23', '132', '63', '47', '1716307200000', '7');
+INSERT INTO `jan` VALUES ('4.08', '株洲', '1.2', '23', '134', '63', '47', '1716393600000', '7');
+INSERT INTO `jan` VALUES ('4.1', '株洲', '1.2', '23', '137', '63', '47', '1716480000000', '7');
+INSERT INTO `jan` VALUES ('4.06', '株洲', '1.2', '23', '136', '63', '46', '1716566400000', '7');
+INSERT INTO `jan` VALUES ('4.06', '株洲', '1.2', '23', '136', '63', '46', '1716652800000', '7');
+
+SET FOREIGN_KEY_CHECKS = 1;

airquility/mar.sql

@@ -0,0 +1,71 @@
+/*
+ Navicat Premium Data Transfer
+
+ Source Server         : AirQui
+ Source Server Type    : MySQL
+ Source Server Version : 80026
+ Source Host           : localhost:3306
+ Source Schema         : airquility
+
+ Target Server Type    : MySQL
+ Target Server Version : 80026
+ File Encoding         : 65001
+
+ Date: 03/06/2024 18:36:48
+*/
+
+SET NAMES utf8mb4;
+SET FOREIGN_KEY_CHECKS = 0;
+
+-- ----------------------------
+-- Table structure for mar
+-- ----------------------------
+DROP TABLE IF EXISTS `mar`;
+CREATE TABLE `mar`  (
+  `ci` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `city` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `co` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `no2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `o3` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm10` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm2.5` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `ptime` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `so2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL
+) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
+
+-- ----------------------------
+-- Records of mar
+-- ----------------------------
+INSERT INTO `mar` VALUES ('4.52', '株洲', '1.3', '27', '88', '78', '61', '1708876800000', '7');
+INSERT INTO `mar` VALUES ('4.52', '株洲', '1.3', '27', '88', '78', '61', '1708963200000', '7');
+INSERT INTO `mar` VALUES ('4.49', '株洲', '1.3', '27', '88', '78', '60', '1709049600000', '7');
+INSERT INTO `mar` VALUES ('4.5', '株洲', '1.3', '27', '89', '78', '60', '1709136000000', '7');
+INSERT INTO `mar` VALUES ('4.5', '株洲', '1.3', '27', '89', '78', '60', '1709222400000', '7');
+INSERT INTO `mar` VALUES ('4.49', '株洲', '1.3', '27', '89', '77', '60', '1709308800000', '7');
+INSERT INTO `mar` VALUES ('4.49', '株洲', '1.3', '27', '89', '77', '60', '1709395200000', '7');
+INSERT INTO `mar` VALUES ('4.46', '株洲', '1.3', '27', '89', '76', '59', '1709481600000', '7');
+INSERT INTO `mar` VALUES ('4.46', '株洲', '1.3', '27', '89', '76', '59', '1709568000000', '7');
+INSERT INTO `mar` VALUES ('4.48', '株洲', '1.3', '27', '88', '77', '60', '1709654400000', '7');
+INSERT INTO `mar` VALUES ('4.49', '株洲', '1.3', '27', '89', '77', '60', '1709740800000', '7');
+INSERT INTO `mar` VALUES ('4.46', '株洲', '1.3', '27', '90', '76', '59', '1709827200000', '7');
+INSERT INTO `mar` VALUES ('4.48', '株洲', '1.3', '27', '92', '76', '59', '1709913600000', '7');
+INSERT INTO `mar` VALUES ('4.49', '株洲', '1.3', '27', '92', '77', '59', '1710000000000', '7');
+INSERT INTO `mar` VALUES ('4.5', '株洲', '1.3', '27', '94', '77', '59', '1710086400000', '7');
+INSERT INTO `mar` VALUES ('4.51', '株洲', '1.3', '27', '96', '77', '59', '1710172800000', '7');
+INSERT INTO `mar` VALUES ('4.51', '株洲', '1.3', '27', '96', '77', '59', '1710259200000', '7');
+INSERT INTO `mar` VALUES ('4.5', '株洲', '1.3', '27', '95', '77', '59', '1710345600000', '7');
+INSERT INTO `mar` VALUES ('4.49', '株洲', '1.3', '27', '95', '76', '59', '1710432000000', '7');
+INSERT INTO `mar` VALUES ('4.46', '株洲', '1.3', '27', '95', '76', '58', '1710518400000', '7');
+INSERT INTO `mar` VALUES ('4.48', '株洲', '1.3', '28', '95', '76', '58', '1710604800000', '7');
+INSERT INTO `mar` VALUES ('4.44', '株洲', '1.3', '27', '95', '75', '58', '1710691200000', '7');
+INSERT INTO `mar` VALUES ('4.44', '株洲', '1.3', '27', '95', '75', '58', '1710777600000', '7');
+INSERT INTO `mar` VALUES ('4.44', '株洲', '1.3', '28', '96', '75', '57', '1710864000000', '7');
+INSERT INTO `mar` VALUES ('4.44', '株洲', '1.3', '28', '96', '75', '57', '1710950400000', '7');
+INSERT INTO `mar` VALUES ('4.43', '株洲', '1.3', '27', '97', '75', '57', '1711036800000', '7');
+INSERT INTO `mar` VALUES ('4.4', '株洲', '1.3', '27', '98', '75', '56', '1711123200000', '7');
+INSERT INTO `mar` VALUES ('4.39', '株洲', '1.3', '27', '98', '74', '56', '1711209600000', '7');
+INSERT INTO `mar` VALUES ('4.39', '株洲', '1.3', '27', '98', '74', '56', '1711296000000', '7');
+INSERT INTO `mar` VALUES ('4.35', '株洲', '1.3', '27', '99', '73', '55', '1711382400000', '7');
+INSERT INTO `mar` VALUES ('4.35', '株洲', '1.3', '27', '100', '73', '55', '1711468800000', '7');
+
+SET FOREIGN_KEY_CHECKS = 1;

airquility/may.sql

@@ -0,0 +1,66 @@
+/*
+ Navicat Premium Data Transfer
+
+ Source Server         : AirQui
+ Source Server Type    : MySQL
+ Source Server Version : 80026
+ Source Host           : localhost:3306
+ Source Schema         : airquility
+
+ Target Server Type    : MySQL
+ Target Server Version : 80026
+ File Encoding         : 65001
+
+ Date: 03/06/2024 13:54:00
+*/
+
+SET NAMES utf8mb4;
+SET FOREIGN_KEY_CHECKS = 0;
+
+-- ----------------------------
+-- Table structure for may
+-- ----------------------------
+DROP TABLE IF EXISTS `may`;
+CREATE TABLE `may`  (
+  `ci` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `city` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `co` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `no2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `o3` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm10` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm2.5` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `ptime` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `so2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL
+) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
+
+-- ----------------------------
+-- Records of may
+-- ----------------------------
+INSERT INTO `may` VALUES ('6.01', '株洲', '0.8', '36', '83', '128', '85', '5/1', '8');
+INSERT INTO `may` VALUES ('5.65', '株洲', '0.9', '32', '80', '117', '82', '5/2', '7');
+INSERT INTO `may` VALUES ('5.13', '株洲', '0.9', '31', '92', '100', '70', '5/3', '7');
+INSERT INTO `may` VALUES ('5.18', '株洲', '1.2', '34', '91', '98', '68', '5/4', '7');
+INSERT INTO `may` VALUES ('5.13', '株洲', '1.2', '36', '90', '95', '66', '5/5', '7');
+INSERT INTO `may` VALUES ('5.3', '株洲', '1.3', '38', '89', '96', '69', '5/6', '8');
+INSERT INTO `may` VALUES ('5.54', '株洲', '1.3', '40', '88', '100', '74', '5/7', '8');
+INSERT INTO `may` VALUES ('5.7', '株洲', '1.3', '39', '87', '105', '78', '5/8', '8');
+INSERT INTO `may` VALUES ('5.8', '株洲', '1.4', '39', '86', '106', '80', '5/9', '8');
+INSERT INTO `may` VALUES ('5.91', '株洲', '1.4', '40', '90', '107', '82', '5/10', '8');
+INSERT INTO `may` VALUES ('5.77', '株洲', '1.4', '39', '89', '104', '79', '5/11', '8');
+INSERT INTO `may` VALUES ('5.76', '株洲', '1.4', '40', '89', '104', '78', '5/12', '8');
+INSERT INTO `may` VALUES ('5.71', '株洲', '1.4', '39', '93', '103', '77', '5/13', '8');
+INSERT INTO `may` VALUES ('5.76', '株洲', '1.4', ',39', '92', '103', '78', '5/14', '9');
+INSERT INTO `may` VALUES ('6.05', '株洲', '1.4', '39', '92', '111', '84', '5/15', '9');
+INSERT INTO `may` VALUES ('6.11', '株洲', '1.4', '39', '92', '113', '86', '5/16', '8');
+INSERT INTO `may` VALUES ('5.97', '株洲', '1.4', '38', '91', '110', '84', '5/17', '8');
+INSERT INTO `may` VALUES ('5.78', '株洲', '1.4', '38', '90', '105', '80', '5/18', '8');
+INSERT INTO `may` VALUES ('5.56', '株洲', '1.4', '37', '90', '100', '76', '5/19', '8');
+INSERT INTO `may` VALUES ('5.47', '株洲', '1.4', '37', '90', '98', '74', '5/20', '8');
+INSERT INTO `may` VALUES ('5.42', '株洲', '1.4', '36', '89', '96', '74', '5/21', '8');
+INSERT INTO `may` VALUES ('5.34', '株洲', '1.4', '36', '89', '94', '72', '5/22', '8');
+INSERT INTO `may` VALUES ('5.23', '株洲', '1.4', '35', '89', '92', '70', '5/23', '8');
+INSERT INTO `may` VALUES ('5.18', '株洲', '1.4', '35', '88', '91', '69', '5/24', '8');
+INSERT INTO `may` VALUES ('5.16', '株洲', '1.4', '36', '88', '90', '68', '5/25', '8');
+INSERT INTO `may` VALUES ('5.11', '株洲', '1.4', '36', '88', '89', '67', '5/26', '8');
+
+SET FOREIGN_KEY_CHECKS = 1;

airquility/timedata.sql

@@ -0,0 +1,187 @@
+/*
+ Navicat Premium Data Transfer
+
+ Source Server         : AirQui
+ Source Server Type    : MySQL
+ Source Server Version : 80026
+ Source Host           : localhost:3306
+ Source Schema         : airquility
+
+ Target Server Type    : MySQL
+ Target Server Version : 80026
+ File Encoding         : 65001
+
+ Date: 03/06/2024 18:38:04
+*/
+
+SET NAMES utf8mb4;
+SET FOREIGN_KEY_CHECKS = 0;
+
+-- ----------------------------
+-- Table structure for timedata
+-- ----------------------------
+DROP TABLE IF EXISTS `timedata`;
+CREATE TABLE `timedata`  (
+  `ci` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `city` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `co` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `no2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `o3` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm10` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `pm2.5` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `ptime` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL,
+  `so2` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL
+) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;
+
+-- ----------------------------
+-- Records of timedata
+-- ----------------------------
+INSERT INTO `timedata` VALUES ('6.01', '株洲', '0.8', '36', '83', '128', '85', '5/26', '8');
+INSERT INTO `timedata` VALUES ('5.65', '株洲', '0.9', '32', '80', '117', '82', '5/25', '7');
+INSERT INTO `timedata` VALUES ('5.13', '株洲', '0.9', '31', '92', '100', '70', '5/24', '7');
+INSERT INTO `timedata` VALUES ('5.18', '株洲', '1.2', '34', '91', '98', '68', '5/23', '7');
+INSERT INTO `timedata` VALUES ('5.13', '株洲', '1.2', '36', '90', '95', '66', '5/22', '7');
+INSERT INTO `timedata` VALUES ('5.3', '株洲', '1.3', '38', '89', '96', '69', '5/21', '8');
+INSERT INTO `timedata` VALUES ('5.54', '株洲', '1.3', '40', '88', '100', '74', '5/20', '8');
+INSERT INTO `timedata` VALUES ('5.7', '株洲', '1.3', '39', '87', '105', '78', '5/19', '8');
+INSERT INTO `timedata` VALUES ('5.8', '株洲', '1.4', '39', '86', '106', '80', '5/18', '8');
+INSERT INTO `timedata` VALUES ('5.91', '株洲', '1.4', '40', '90', '107', '82', '5/17', '8');
+INSERT INTO `timedata` VALUES ('5.77', '株洲', '1.4', '39', '89', '104', '79', '5/16', '8');
+INSERT INTO `timedata` VALUES ('5.76', '株洲', '1.4', '40', '89', '104', '78', '5/15', '8');
+INSERT INTO `timedata` VALUES ('5.71', '株洲', '1.4', '39', '93', '103', '77', '5/14', '8');
+INSERT INTO `timedata` VALUES ('5.76', '株洲', '1.4', '39', '92', '103', '78', '5/13', '9');
+INSERT INTO `timedata` VALUES ('6.05', '株洲', '1.4', '39', '92', '111', '84', '5/12', '9');
+INSERT INTO `timedata` VALUES ('6.11', '株洲', '1.4', '39', '92', '113', '86', '5/11', '8');
+INSERT INTO `timedata` VALUES ('5.97', '株洲', '1.4', '38', '91', '110', '84', '5/10', '8');
+INSERT INTO `timedata` VALUES ('5.78', '株洲', '1.4', '38', '90', '105', '80', '5/9', '8');
+INSERT INTO `timedata` VALUES ('5.56', '株洲', '1.4', '37', '90', '100', '76', '5/8', '8');
+INSERT INTO `timedata` VALUES ('5.47', '株洲', '1.4', '37', '90', '98', '74', '5/7', '8');
+INSERT INTO `timedata` VALUES ('5.42', '株洲', '1.4', '36', '89', '96', '74', '5/6', '8');
+INSERT INTO `timedata` VALUES ('5.34', '株洲', '1.4', '36', '89', '94', '72', '5/5', '8');
+INSERT INTO `timedata` VALUES ('5.23', '株洲', '1.4', '35', '89', '92', '70', '5/4', '8');
+INSERT INTO `timedata` VALUES ('5.18', '株洲', '1.4', '35', '88', '91', '69', '5/3', '8');
+INSERT INTO `timedata` VALUES ('5.16', '株洲', '1.4', '36', '88', '90', '68', '5/2', '8');
+INSERT INTO `timedata` VALUES ('5.11', '株洲', '1.4', '36', '88', '89', '67', '4/30', '8');
+INSERT INTO `timedata` VALUES ('5.11', '株洲', '1.4', '36', '88', '89', '67', '5/1', '8');
+INSERT INTO `timedata` VALUES ('5.13', '株洲', '1.4', '37', '88', '89', '67', '4/29', '8');
+INSERT INTO `timedata` VALUES ('5.17', '株洲', '1.4', '37', '87', '90', '68', '4/28', '8');
+INSERT INTO `timedata` VALUES ('5.11', '株洲', '1.4', '37', '87', '88', '67', '4/27', '8');
+INSERT INTO `timedata` VALUES ('5.07', '株洲', '1.4', '37', '87', '87', '66', '4/26', '8');
+INSERT INTO `timedata` VALUES ('4.95', '株洲', '1.3', '36', '87', '85', '65', '4/25', '7');
+INSERT INTO `timedata` VALUES ('4.9', '株洲', '1.3', '36', '86', '83', '64', '4/24', '7');
+INSERT INTO `timedata` VALUES ('4.8', '株洲', '1.3', '35', '86', '82', '62', '4/23', '7');
+INSERT INTO `timedata` VALUES ('4.79', '株洲', '1.3', '35', '86', '81', '62', '4/22', '7');
+INSERT INTO `timedata` VALUES ('4.71', '株洲', '1.3', '34', '86', '80', '61', '4/21', '7');
+INSERT INTO `timedata` VALUES ('4.66', '株洲', '1.3', '34', '85', '79', '60', '4/20', '7');
+INSERT INTO `timedata` VALUES ('4.69', '株洲', '1.3', '34', '85', '79', '61', '4/19', '7');
+INSERT INTO `timedata` VALUES ('4.7', '株洲', '1.3', '33', '87', '79', '62', '4/18', '7');
+INSERT INTO `timedata` VALUES ('4.82', '株洲', '1.3', '33', '90', '82', '64', '4/17', '7');
+INSERT INTO `timedata` VALUES ('5', '株洲', '1.3', '33', '89', '87', '68', '4/16', '7');
+INSERT INTO `timedata` VALUES ('5.07', '株洲', '1.3', '32', '94', '88', '69', '4/15', '8');
+INSERT INTO `timedata` VALUES ('5.06', '株洲', '1.3', '32', '93', '88', '69', '4/14', '8');
+INSERT INTO `timedata` VALUES ('4.99', '株洲', '1.3', '31', '92', '87', '68', '4/12', '8');
+INSERT INTO `timedata` VALUES ('4.99', '株洲', '1.3', '31', '92', '87', '68', '4/13', '8');
+INSERT INTO `timedata` VALUES ('4.95', '株洲', '1.3', '31', '92', '86', '67', '4/11', '8');
+INSERT INTO `timedata` VALUES ('4.86', '株洲', '1.3', '30', '91', '85', '66', '4/10', '7');
+INSERT INTO `timedata` VALUES ('4.84', '株洲', '1.3', '30', '90', '84', '66', '4/9', '7');
+INSERT INTO `timedata` VALUES ('4.77', '株洲', '1.3', '29', '90', '83', '65', '4/8', '7');
+INSERT INTO `timedata` VALUES ('4.74', '株洲', '1.3', '29', '90', '83', '64', '4/7', '7');
+INSERT INTO `timedata` VALUES ('4.69', '株洲', '1.3', '29', '89', '82', '63', '4/6', '7');
+INSERT INTO `timedata` VALUES ('4.63', '株洲', '1.3', '28', '89', '81', '62', '4/5', '7');
+INSERT INTO `timedata` VALUES ('4.61', '株洲', '1.3', '28', '89', '80', '62', '4/4', '7');
+INSERT INTO `timedata` VALUES ('4.57', '株洲', '1.3', '28', '89', '79', '61', '4/3', '7');
+INSERT INTO `timedata` VALUES ('4.55', '株洲', '1.3', '27', '89', '79', '61', '4/2', '7');
+INSERT INTO `timedata` VALUES ('4.52', '株洲', '1.3', '27', '88', '78', '61', '3/30', '7');
+INSERT INTO `timedata` VALUES ('4.52', '株洲', '1.3', '27', '88', '78', '61', '3/31', '7');
+INSERT INTO `timedata` VALUES ('4.52', '株洲', '1.3', '27', '88', '78', '61', '4/1', '7');
+INSERT INTO `timedata` VALUES ('4.49', '株洲', '1.3', '27', '88', '78', '60', '3/29', '7');
+INSERT INTO `timedata` VALUES ('4.5', '株洲', '1.3', '27', '89', '78', '60', '3/27', '7');
+INSERT INTO `timedata` VALUES ('4.5', '株洲', '1.3', '27', '89', '78', '60', '3/28', '7');
+INSERT INTO `timedata` VALUES ('4.49', '株洲', '1.3', '27', '89', '77', '60', '3/21', '7');
+INSERT INTO `timedata` VALUES ('4.49', '株洲', '1.3', '27', '89', '77', '60', '3/25', '7');
+INSERT INTO `timedata` VALUES ('4.46', '株洲', '1.3', '27', '89', '76', '59', '3/23', '7');
+INSERT INTO `timedata` VALUES ('4.46', '株洲', '1.3', '27', '89', '76', '59', '3/24', '7');
+INSERT INTO `timedata` VALUES ('4.48', '株洲', '1.3', '27', '88', '77', '60', '3/22', '7');
+INSERT INTO `timedata` VALUES ('4.49', '株洲', '1.3', '27', '89', '77', '60', '3/26', '7');
+INSERT INTO `timedata` VALUES ('4.46', '株洲', '1.3', '27', '90', '76', '59', '3/20', '7');
+INSERT INTO `timedata` VALUES ('4.48', '株洲', '1.3', '27', '92', '76', '59', '3/19', '7');
+INSERT INTO `timedata` VALUES ('4.49', '株洲', '1.3', '27', '92', '77', '59', '3/18', '7');
+INSERT INTO `timedata` VALUES ('4.5', '株洲', '1.3', '27', '94', '77', '59', '3/17', '7');
+INSERT INTO `timedata` VALUES ('4.51', '株洲', '1.3', '27', '96', '77', '59', '3/15', '7');
+INSERT INTO `timedata` VALUES ('4.51', '株洲', '1.3', '27', '96', '77', '59', '3/16', '7');
+INSERT INTO `timedata` VALUES ('4.5', '株洲', '1.3', '27', '95', '77', '59', '3/14', '7');
+INSERT INTO `timedata` VALUES ('4.49', '株洲', '1.3', '27', '95', '76', '59', '3/13', '7');
+INSERT INTO `timedata` VALUES ('4.46', '株洲', '1.3', '27', '95', '76', '58', '3/12', '7');
+INSERT INTO `timedata` VALUES ('4.48', '株洲', '1.3', '28', '95', '76', '58', '3/11', '7');
+INSERT INTO `timedata` VALUES ('4.44', '株洲', '1.3', '27', '95', '75', '58', '3/9', '7');
+INSERT INTO `timedata` VALUES ('4.44', '株洲', '1.3', '27', '95', '75', '58', '3/10', '7');
+INSERT INTO `timedata` VALUES ('4.44', '株洲', '1.3', '28', '96', '75', '57', '3/7', '7');
+INSERT INTO `timedata` VALUES ('4.44', '株洲', '1.3', '28', '96', '75', '57', '3/8', '7');
+INSERT INTO `timedata` VALUES ('4.43', '株洲', '1.3', '27', '97', '75', '57', '3/6', '7');
+INSERT INTO `timedata` VALUES ('4.4', '株洲', '1.3', '27', '98', '75', '56', '3/5', '7');
+INSERT INTO `timedata` VALUES ('4.39', '株洲', '1.3', '27', '98', '74', '56', '3/3', '7');
+INSERT INTO `timedata` VALUES ('4.39', '株洲', '1.3', '27', '98', '74', '56', '3/4', '7');
+INSERT INTO `timedata` VALUES ('4.35', '株洲', '1.3', '27', '99', '73', '55', '3/2', '7');
+INSERT INTO `timedata` VALUES ('4.35', '株洲', '1.3', '27', '100', '73', '55', '3/1', '7');
+INSERT INTO `timedata` VALUES ('4.36', '株洲', '1.3', '27', '101', '73', '55', '2/29', '7');
+INSERT INTO `timedata` VALUES ('4.33', '株洲', '1.3', '27', '102', '72', '54', '2/28', '7');
+INSERT INTO `timedata` VALUES ('4.3', '株洲', '1.3', '26', '102', '72', '54', '2/27', '7');
+INSERT INTO `timedata` VALUES ('4.33', '株洲', '1.3', '26', '107', '72', '54', '2/26', '7');
+INSERT INTO `timedata` VALUES ('4.27', '株洲', '1.3', '26', '106', '71', '53', '2/25', '7');
+INSERT INTO `timedata` VALUES ('4.3', '株洲', '1.3', '26', '111', '71', '53', '2/24', '7');
+INSERT INTO `timedata` VALUES ('4.29', '株洲', '1.3', '26', '110', '70', '53', '2/21', '7');
+INSERT INTO `timedata` VALUES ('4.29', '株洲', '1.3', '26', '110', '70', '53', '2/22', '7');
+INSERT INTO `timedata` VALUES ('4.29', '株洲', '1.3', '26', '110', '70', '53', '2/23', '7');
+INSERT INTO `timedata` VALUES ('4.28', '株洲', '1.3', '26', '109', '70', '53', '2/20', '7');
+INSERT INTO `timedata` VALUES ('4.28', '株洲', '1.3', '26', '108', '70', '53', '2/19', '7');
+INSERT INTO `timedata` VALUES ('4.3', '株洲', '1.3', '26', '112', '70', '53', '2/18', '7');
+INSERT INTO `timedata` VALUES ('4.29', '株洲', '1.3', '26', '112', '69', '53', '2/16', '7');
+INSERT INTO `timedata` VALUES ('4.29', '株洲', '1.3', '26', '112', '69', '53', '2/17', '7');
+INSERT INTO `timedata` VALUES ('4.27', '株洲', '1.3', '26', '112', '69', '52', '2/15', '7');
+INSERT INTO `timedata` VALUES ('4.26', '株洲', '1.3', '26', '111', '69', '52', '2/14', '7');
+INSERT INTO `timedata` VALUES ('4.26', '株洲', '1.3', '26', '110', '69', '52', '2/13', '7');
+INSERT INTO `timedata` VALUES ('4.24', '株洲', '1.3', '26', '110', '68', '52', '2/12', '7');
+INSERT INTO `timedata` VALUES ('4.25', '株洲', '1.3', '26', '112', '68', '52', '2/11', '7');
+INSERT INTO `timedata` VALUES ('4.22', '株洲', '1.3', '25', '112', '68', '52', '2/9', '7');
+INSERT INTO `timedata` VALUES ('4.22', '株洲', '1.3', '25', '112', '68', '52', '2/10', '7');
+INSERT INTO `timedata` VALUES ('4.19', '株洲', '1.3', '25', '112', '68', '51', '2/8', '7');
+INSERT INTO `timedata` VALUES ('4.18', '株洲', '1.3', '25', '112', '67', '51', '2/7', '7');
+INSERT INTO `timedata` VALUES ('4.16', '株洲', '1.2', '25', '112', '67', '51', '2/5', '7');
+INSERT INTO `timedata` VALUES ('4.16', '株洲', '1.2', '25', '112', '67', '51', '2/6', '7');
+INSERT INTO `timedata` VALUES ('4.13', '株洲', '1.2', '25', '111', '66', '51', '2/4', '7');
+INSERT INTO `timedata` VALUES ('4.12', '株洲', '1.2', '25', '113', '66', '50', '2/1', '7');
+INSERT INTO `timedata` VALUES ('4.12', '株洲', '1.2', '25', '113', '66', '50', '2/2', '7');
+INSERT INTO `timedata` VALUES ('4.12', '株洲', '1.2', '25', '113', '66', '50', '2/3', '7');
+INSERT INTO `timedata` VALUES ('4.13,', '株洲', '1.2', '25', '115', '66', '50', '1/31', '7');
+INSERT INTO `timedata` VALUES ('4.12', '株洲', '1.2', '25', '114', '66', '50', '1/30', '7');
+INSERT INTO `timedata` VALUES ('4.14', '株洲', '1.2', '25', '119', '65', '50', '1/28', '7');
+INSERT INTO `timedata` VALUES ('4.14', '株洲', '1.2', '25', '119', '65', '50', '1/29', '7');
+INSERT INTO `timedata` VALUES ('4.11', '株洲', '1.2', '25', '118', '65', '49', '1/27', '7');
+INSERT INTO `timedata` VALUES ('4.09', '株洲', '1.2', '24', '118', '65', '49', '1/26', '7');
+INSERT INTO `timedata` VALUES ('4.06', '株洲', '1.2', '24', '117', '64', '49', '1/25', '7');
+INSERT INTO `timedata` VALUES ('4.05', '株洲', '1.2', '24', '116', '64', '49', '1/23', '7');
+INSERT INTO `timedata` VALUES ('4.05', '株洲', '1.2', '24', '116', '64', '49', '1/24', '7');
+INSERT INTO `timedata` VALUES ('4.04', '株洲', '1.2', '24', '116', '63', '49', '1/22', '7');
+INSERT INTO `timedata` VALUES ('4.01', '株洲', '1.2', '24', '115', '63', '48', '1/21', '7');
+INSERT INTO `timedata` VALUES ('4', '株洲', '1.2', '24', '114', '63', '48', '1/20', '7');
+INSERT INTO `timedata` VALUES ('4.03', '株洲', '1.2', '24', '119', '63', '48', '1/19', '7');
+INSERT INTO `timedata` VALUES ('4.0', '株洲', '1.2', '24', '124', '63', '48', '1/18', '7');
+INSERT INTO `timedata` VALUES ('4.07', '株洲', '1.2', '24', '124', '63', '48', '1/17', '7');
+INSERT INTO `timedata` VALUES ('4.06', '株洲', '1.2', '24', '123', '63', '48', '1/16', '7');
+INSERT INTO `timedata` VALUES ('4.07', '株洲', '1.2', '24', '125', '63', '48', '1/15', '7');
+INSERT INTO `timedata` VALUES ('4.09', '株洲', '1.2', '24', '126', '64', '48', '1/13', '7');
+INSERT INTO `timedata` VALUES ('4.09', '株洲', '1.2', '24', '126', '64', '48', '1/14', '7');
+INSERT INTO `timedata` VALUES ('4.09', '株洲', '1.2', '24', '127', '64', '48', '1/12', '7');
+INSERT INTO `timedata` VALUES ('4.11', '株洲', '1.2', '24', '130', '64', '48', '1/11', '7');
+INSERT INTO `timedata` VALUES ('4.12', '株洲', '1.2', '24', '132', '64', '48', '1/10', '7');
+INSERT INTO `timedata` VALUES ('4.1', '株洲', '1.2', '24', '133', '64', '47', '1/9', '7');
+INSERT INTO `timedata` VALUES ('4.09', '株洲', '1.2', '24', '132', '64', '47', '1/6', '7');
+INSERT INTO `timedata` VALUES ('4.09', '株洲', '1.2', '24', '132', '64', '47', '1/7', '7');
+INSERT INTO `timedata` VALUES ('4.09', '株洲', '1.2', '24', '132', '64', '47', '1/8', '7');
+INSERT INTO `timedata` VALUES ('4.06', '株洲', '1.2', '23', '132', '63', '47', '1/5', '7');
+INSERT INTO `timedata` VALUES ('4.08', '株洲', '1.2', '23', '134', '63', '47', '1/4', '7');
+INSERT INTO `timedata` VALUES ('4.1', '株洲', '1.2', '23', '137', '63', '47', '1/3', '7');
+INSERT INTO `timedata` VALUES ('4.06', '株洲', '1.2', '23', '136', '63', '47', '1/2', '7');
+INSERT INTO `timedata` VALUES ('4.06', '株洲', '1.2', '23', '136', '63', '46', '1/1', '7');
+
+SET FOREIGN_KEY_CHECKS = 1;