29 lines
738 B
Python
29 lines
738 B
Python
import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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num_time_step = 200
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num_iter = 10
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env_data = pd.DataFrame(pd.read_excel('env_data.xlsx', engine='openpyxl', sheet_name=0))
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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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lst_column = lst_df[0].columns[1:]
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for str_col in lst_column:
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x = np.arange(num_time_step+1)
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for df in lst_df:
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y = np.array(df[str_col]).flatten()
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plt.xlabel('t')
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plt.ylabel(str_col)
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plt.plot(x, y)
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# plt.show()
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# plt.close()
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plt.savefig(f'{str_col}.pdf', bbox_inches="tight")
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