Changes:递归均值计算以及测试代码完成

average_x.py

@@ -0,0 +1,29 @@
+from algorithm import algorithm
+import json
+import ray
+
+@ray.remote
+class average_x(algorithm):
+    def __init__(self):
+        self.config_dict_ = None
+        self.config_ = None
+        self.average_number_ = 10
+        self.present_number_ = 0
+        self.avg_ = 0
+
+    def set_config(self, config):
+        self.config_ = config
+        self.config_dict_ = json.loads(self.config_)
+        self.average_number_ = self.config_dict_["AVERAGE_NUMBER"]
+        self.init_flag_ = False
+
+    def config(self):
+        return self.config_
+
+    def eval(self, value):
+        if self.init_flag_ == False:
+            self.init_flag_ = True
+            self.avg_ = value
+        else:
+            self.avg_ = self.avg_ * (self.average_number_ - 1)/self.average_number_ + value / self.average_number_
+        return self.avg_

average_x_test_csv.py

@@ -0,0 +1,31 @@
+import pandas as pd
+from average_x import average_x
+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]
+cow_len = origin_data.shape[1]
+average_data = origin_data
+algorithm_average = average_x.remote()
+
+cow_name = "G1.TTXD1_3"
+contrast_data = pd.DataFrame()
+contrast_data[cow_name+'_origin'] = origin_data[cow_name]
+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)
+
+print(average_data.loc[:, cow_name])
+contrast_data[cow_name+'_average_x'] = 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_x_data.csv", index=False)
+
+
+# 以下均为测试性能用
+# print(algorithm_step.config_)