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.remote()

cow_name = "G1.TTXD1_3"
contrast_data = pd.DataFrame()
contrast_data[cow_name+'_origin'] = origin_data[cow_name]
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):
    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_)