31 lines
1.0 KiB
Python
31 lines
1.0 KiB
Python
import pandas as pd
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from variance_x import variance_x
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import ray
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ray.init()
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RAY_DISABLE_MEMORY_MONITOR=1
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filepath = "D:/python_project_data/1.csv"
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origin_data = pd.read_csv(filepath)
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row_len = origin_data.shape[0]
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cow_len = origin_data.shape[1]
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variance_data = origin_data
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algorithm_variance_x = variance_x.remote()
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cow_name = "G1.TTXD1_3"
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contrast_data = pd.DataFrame()
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contrast_data[cow_name+'_origin'] = origin_data[cow_name]
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algorithm_variance_x.set_config.remote('{"WINDOW_LENGTH": 5 }')
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# algorithm_step.set_config('{"CYCLE_TIME_BASE": 5 }')
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for i in range(0,row_len):
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futures=algorithm_variance_x.eval.remote(origin_data.loc[i,cow_name])
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variance_data.loc[i, cow_name]=ray.get(futures)
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print(variance_data.loc[:, cow_name])
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contrast_data[cow_name+'_variance_x'] = variance_data[cow_name]
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# average_data.to_csv("D:/python_project_data/1_disturb.csv", index=False)
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contrast_data.to_csv("D:/python_project_data/variance_data_x.csv", index=False)
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ray.shutdown()
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# 以下均为测试性能用
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# print(algorithm_step.config_) |