完成第一次测试

post.py

@@ -1,21 +1,68 @@
 import socket
 import random
 import time
+import pandas as pd
+import numpy as np
+
+def data_clean(data, is_column=False):
+    """_summary_
+
+    Args:
+        data (_type_): csv数据
+        is_column (bool, optional): 清除含有NaN数据的列. Defaults to False.即清除含有NaN数据的行
+
+    Returns:
+        _type_: 清洗过的数据
+    """
+    if not is_column:
+        data = data.dropna(axis=0)
+        return data
+    else:
+        data = data.dropna(axis=1)
+        return data
+      
+def data_load(data_path, is_column=False):
+    """
+    数据加载
+    data_path: 数据路径
+    is_column: 是否是列数据
+    return:X,Y
+    """
+    # 读取csv文件
+    df = pd.read_csv(data_path)
+
+    # 进行数据清洗
+    data_clean(df, is_column)
+    df = df[df['output'] == 1]
+
+    # 去除第一列
+    df = df.drop(df.columns[0], axis=1)
+
+    # 初始化X,Y
+    X= []
+
+    # 遍历DataFrame的每一行
+    for index, row in df.iterrows():
+        # 获取前127个数据项
+        X.append(row.iloc[0:129])
+
+    return np.array(X)
+
+# 输入需要发送的数据
+data = data_load('data\PowerQualityDistributionDataset1.csv')
 
 # 创建一个socket：
 s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
 # 建立连接:
 s.connect(('localhost', 9996))
 while True:
-    try:
-        # 输入需要发送的数据
-        data = str(random.randint(1, 10))
-        time.sleep(0.1)
-        if data.lower() == 'exit':
+    for i in data:
+      for j in i:
+        try:
+            time.sleep(0.5)
+            # 发送数据:
+            s.send((str(j)).encode())
+        except KeyboardInterrupt:
             break
-        # 发送数据:
-        s.send(data.encode())
-    except KeyboardInterrupt:
-        break
 # 关闭连接
 s.close()

test.txt

@@ -1 +1 @@
-#
+#3293.482471