53 lines
2.1 KiB
Python
53 lines
2.1 KiB
Python
import settle_prediction_steps_main
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import pandas as pd
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import os
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input_dir = 'data_1'
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output_dir = 'output_1'
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input_files = []
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df_overall = pd.DataFrame(columns=['File', 'Data_usage',
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'RMSE_hyper_original',
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'RMSE_hyper_nonlinear',
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'Final_error_hyper_original',
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'Final_error_hyper_nonlinear'])
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df_multi_step = pd.DataFrame(columns=['File', 'Data_usage',
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'RMSE_hyper_original',
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'RMSE_hyper_nonlinear',
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'RMSE_step',
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'Final_error_hyper_original',
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'Final_error_hyper_nonlinear',
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'Final_error_step'])
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for (root, directories, files) in os.walk(input_dir):
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for file in files:
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file_path = os.path.join(root, file)
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input_files.append(file_path)
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for input_file in input_files:
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for i in range(20, 100, 10):
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RETURN_VALUES = settle_prediction_steps_main.\
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run_settle_prediction(input_file, output_dir, i, 100, False, False)
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df_overall.loc[len(df_overall.index)] = [input_file, i,
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RETURN_VALUES[0],
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RETURN_VALUES[1],
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RETURN_VALUES[3],
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RETURN_VALUES[4]]
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if RETURN_VALUES[6]:
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df_multi_step.loc[len(df_overall.index)] = [input_file, i,
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RETURN_VALUES[0],
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RETURN_VALUES[1],
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RETURN_VALUES[2],
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RETURN_VALUES[3],
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RETURN_VALUES[4],
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RETURN_VALUES[5]]
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# 에러 파일 출력
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df_overall.to_csv('Error_overall.csv')
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df_multi_step.to_csv('Error_multi_step.csv')
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