From cbf24656f908f699106920f09fd11e78bf77de3c Mon Sep 17 00:00:00 2001
From: Rance4396 <2437708352@qq.com>
Date: Fri, 27 May 2022 16:44:49 +0800
Subject: [PATCH] =?UTF-8?q?Changes:=E8=BF=AD=E4=BB=A3=E6=96=B9=E5=B7=AE?=
 =?UTF-8?q?=E8=AE=A1=E7=AE=97?=
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---
 variance_x.py          | 32 ++++++++++++++++++++++++++++++++
 variance_x_test_csv.py | 31 +++++++++++++++++++++++++++++++
 2 files changed, 63 insertions(+)
 create mode 100644 variance_x.py
 create mode 100644 variance_x_test_csv.py

diff --git a/variance_x.py b/variance_x.py
new file mode 100644
index 0000000..6dd8ec5
--- /dev/null
+++ b/variance_x.py
@@ -0,0 +1,32 @@
+from algorithm import algorithm
+import json
+import ray
+
+@ray.remote
+class variance_x(algorithm):
+    def __init__(self):
+        self.config_dict_ = None
+        self.config_ = None
+        self.window_length_ = 10
+        self.avg_ = 0
+        self.var_ = 0
+
+    def set_config(self, config):
+        self.config_ = config
+        self.config_dict_ = json.loads(self.config_)
+        self.window_length_ = self.config_dict_["WINDOW_LENGTH"]
+        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
+            self.var_ = 0
+        else:
+            present_avg_ = self.avg_ * (self.window_length_ - 1)/self.window_length_ + value / self.window_length_
+            self.var_ = self.var_ +(value - present_avg_) * (value-self.avg_)
+            self.avg_ = present_avg_
+        return self.var_
diff --git a/variance_x_test_csv.py b/variance_x_test_csv.py
new file mode 100644
index 0000000..4dedcf6
--- /dev/null
+++ b/variance_x_test_csv.py
@@ -0,0 +1,31 @@
+import pandas as pd
+from variance_x import variance_x
+import ray
+
+ray.init()
+
+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]
+variance_data = origin_data
+algorithm_variance_x = variance_x.remote()
+
+cow_name = "G1.TTXD1_3"
+contrast_data = pd.DataFrame()
+contrast_data[cow_name+'_origin'] = origin_data[cow_name]
+algorithm_variance_x.set_config.remote('{"WINDOW_LENGTH": 5 }')
+# algorithm_step.set_config('{"CYCLE_TIME_BASE": 5 }')
+for i in range(0,row_len):
+    futures=algorithm_variance_x.eval.remote(origin_data.loc[i,cow_name])
+    variance_data.loc[i, cow_name]=ray.get(futures)
+
+print(variance_data.loc[:, cow_name])
+contrast_data[cow_name+'_variance_x'] = variance_data[cow_name]
+# average_data.to_csv("D:/python_project_data/1_disturb.csv", index=False)
+contrast_data.to_csv("D:/python_project_data/variance_data_x.csv", index=False)
+
+
+# 以下均为测试性能用
+# print(algorithm_step.config_)
\ No newline at end of file