From dbd5240a1a99928b07b82f77f2c607fb4ccfefb8 Mon Sep 17 00:00:00 2001
From: Rance4396 <2437708352@qq.com>
Date: Tue, 17 May 2022 16:50:49 +0800
Subject: [PATCH] =?UTF-8?q?Changes:=E5=A2=9E=E5=8A=A0=E4=BA=86=E8=87=AA?=
 =?UTF-8?q?=E5=8A=A8=E7=94=9F=E6=88=90=E4=BF=AE=E6=94=B9=E6=95=B0=E6=8D=AE?=
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---
 cycle.py          |  3 ++-
 cycle_test_csv.py | 14 +++++++++-----
 excursion.py      |  3 ++-
 ray_example.py    | 18 ++++++++++++++++++
 step.py           |  3 ++-
 step_test.py      | 17 ++++++++++-------
 white_noise.py    |  3 ++-
 7 files changed, 45 insertions(+), 16 deletions(-)
 create mode 100644 ray_example.py

diff --git a/cycle.py b/cycle.py
index 32a23f0..188a445 100644
--- a/cycle.py
+++ b/cycle.py
@@ -1,8 +1,9 @@
 from algorithm import algorithm
 import json
 import math
+import ray
 
-
+@ray.remote
 class cycle(algorithm):
     def __init__(self):
         self.config_dict_ = None
diff --git a/cycle_test_csv.py b/cycle_test_csv.py
index 8f4c6d8..0062b53 100644
--- a/cycle_test_csv.py
+++ b/cycle_test_csv.py
@@ -1,25 +1,29 @@
 import pandas as pd
 from cycle import cycle
+import ray
 
+ray.init()
 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]
 disturb_data = origin_data
-algorithm_step = cycle()
+algorithm_step = cycle.remote()
 
 cow_name = "G1.TTXD1_3"
 contrast_data = pd.DataFrame()
 contrast_data[cow_name+'_origin'] = origin_data[cow_name]
-algorithm_step.set_config('{"CYCLE_AMPLITUDE_BASE": 200 , "CYCLE_TIME_BASE": 5 ,"CYCLE_START_ANGLE_BASE": 3.14}')
+algorithm_step.set_config.remote('{"CYCLE_AMPLITUDE_BASE": 200 , "CYCLE_TIME_BASE": 5 ,"CYCLE_START_ANGLE_BASE": 3.14}')
 # algorithm_step.set_config('{"CYCLE_TIME_BASE": 5 }')
 for i in range(0,row_len):
-    disturb_data.loc[i,cow_name]=algorithm_step.eval(origin_data.loc[i,cow_name],i)
-print(disturb_data)
+    futures=algorithm_step.eval.remote(origin_data.loc[i,cow_name],i)
+    disturb_data.loc[i,cow_name]=ray.get(futures)
+
+print(disturb_data.loc[:,cow_name])
 contrast_data[cow_name+'_disturb'] = disturb_data[cow_name]
 disturb_data.to_csv("D:/python_project_data/1_disturb.csv", index=False)
 contrast_data.to_csv("D:/python_project_data/contrast_data.csv", index=False)
 
 
 # 以下均为测试性能用
-print(algorithm_step.config_)
\ No newline at end of file
+# print(algorithm_step.config_)
\ No newline at end of file
diff --git a/excursion.py b/excursion.py
index 27c81c9..99a3a01 100644
--- a/excursion.py
+++ b/excursion.py
@@ -1,7 +1,8 @@
 from algorithm import algorithm
 import json
+import ray
 
-
+@ray.remote
 class excursion(algorithm):
     def __init__(self):
         self.config_dict_ = None
diff --git a/ray_example.py b/ray_example.py
new file mode 100644
index 0000000..1a34564
--- /dev/null
+++ b/ray_example.py
@@ -0,0 +1,18 @@
+import ray
+ray.init()
+
+@ray.remote
+class Counter(object):
+    def __init__(self):
+        self.n = 0
+
+    def increment(self):
+        self.n += 1
+
+    def read(self):
+        return self.n
+
+counters = [Counter.remote() for i in range(4)]
+[c.increment.remote() for c in counters]
+futures = [c.read.remote() for c in counters]
+print(ray.get(futures))
diff --git a/step.py b/step.py
index fc7e5a8..f1f863c 100644
--- a/step.py
+++ b/step.py
@@ -1,7 +1,8 @@
 from algorithm import algorithm
 import json
+import ray
 
-
+@ray.remote
 class step(algorithm):
     def __init__(self):
         self.config_dict_ = None
diff --git a/step_test.py b/step_test.py
index 9f4900b..25ae4d4 100644
--- a/step_test.py
+++ b/step_test.py
@@ -1,14 +1,17 @@
 import pandas as pd
 from step import step
+import ray
+ray.init()
 
-filepath = "D:/python_project/TurbineExhaustTemperatureTheromcouple-FourWorkingCondition.xlsx"
-origin_data = pd.read_excel(filepath,sheet_name='s4_ttxd')
+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]
 disturb_data = origin_data
-algorithm_step = step()
-cow_name = "ttxd_12_1"
-algorithm_step.set_config('{"STEP_AMPLITUDE_BASE": 1.3}')
+algorithm_step = step.remote()
+cow_name = "G1.TTXD1_3"
+algorithm_step.set_config.remote('{"STEP_AMPLITUDE_BASE": 1.3}')
 for i in range(0,row_len):
-    disturb_data.loc[i,cow_name]=algorithm_step.eval(origin_data.loc[i,cow_name])
-print(disturb_data)
\ No newline at end of file
+    futures=algorithm_step.eval.remote(origin_data.loc[i,cow_name])
+    disturb_data.loc[i, cow_name] = ray.get(futures)
+print(disturb_data.loc[:,cow_name])
\ No newline at end of file
diff --git a/white_noise.py b/white_noise.py
index 0831132..0f6fcfb 100644
--- a/white_noise.py
+++ b/white_noise.py
@@ -2,8 +2,9 @@ from random import random
 import numpy as np
 from algorithm import algorithm
 import json
+import ray
 
-
+@ray.remote
 class white_noise(algorithm):
     def __init__(self):
         self.config_dict_ = None