2022-10-31 15:05:22 +08:00
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import numpy as np
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import pandas as pd
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2023-01-15 21:53:12 +08:00
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num_time_step = 200
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2022-10-31 15:05:22 +08:00
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num_iter = 10
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env_data = pd.DataFrame(pd.read_excel('env_data.xlsx', engine='openpyxl'))
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assert env_data.shape[0] == num_iter * (num_time_step + 1)
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lst_df = []
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for i in range(num_iter):
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df_tmp = env_data.iloc[i * (num_time_step + 1): (i + 1) * (num_time_step + 1), 1:]
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lst_df.append(df_tmp)
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# df_tmp = env_data.iloc[1: 21]
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# lst_df.append(df_tmp)
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x = np.array(env_data[['t']])
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y = np.array(env_data[['out_w_avg_salary']])
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import matplotlib.pyplot as plt
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plt.xlabel('t')
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plt.ylabel('out_w_avg_salary')
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plt.plot(x, y)
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plt.show()
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