Changes:完整窗口均值计算以及对应测试代码完成

average.py

@@ -26,12 +26,16 @@ class average(algorithm):
         self.present_number_ = len(self.window_1_)
         if self.present_number_ < self.average_number_:
             self.window_1_.append(value)
-            return
-        else:
             self.sum = 0
             for i in self.window_1_:
                 self.sum = self.sum + i
             self.average = self.sum / len(self.window_1_)
+            return self.average
+        else:
+            self.sum = 0
             del self.window_1_[0]
             self.window_1_.append(value)
+            for i in self.window_1_:
+                self.sum = self.sum + i
+            self.average = self.sum / len(self.window_1_)
             return self.average

average_test_csv.py

@@ -3,6 +3,8 @@ from average import average
 import ray
 
 ray.init()
+
+ray.RAY_DISABLE_MEMORY_MONITOR=1
 filepath = "D:/python_project_data/1.csv"
 origin_data = pd.read_csv(filepath)
 row_len = origin_data.shape[0]
@@ -17,9 +19,9 @@ algorithm_average.set_config.remote('{"AVERAGE_NUMBER": 5 }')
 # algorithm_step.set_config('{"CYCLE_TIME_BASE": 5 }')
 for i in range(0,row_len):
     futures=algorithm_average.eval.remote(origin_data.loc[i,cow_name])
-    average_data.loc[i,cow_name]=ray.get(futures)
+    average_data.loc[i, cow_name]=ray.get(futures)
 
-print(average_data.loc[:,cow_name])
+print(average_data.loc[:, cow_name])
 contrast_data[cow_name+'_average'] = average_data[cow_name]
 # average_data.to_csv("D:/python_project_data/1_disturb.csv", index=False)
 contrast_data.to_csv("D:/python_project_data/average_data.csv", index=False)