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38 lines
1.1 KiB
38 lines
1.1 KiB
import matplotlib.pyplot as plt
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import pandas as pd
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go = 'y'
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parameters = 'slope,intercept,beta0,beta1,Cphi'.split(',')
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while go == 'y':
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go = input('continue? ')
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plt.close('all')
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df = pd.read_csv('outputs/iterative_fitter_output_df.csv')
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info_cols = {parameter: [] for parameter in parameters}
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for col in df.columns:
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for parameter in parameters:
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if parameter in col:
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info_cols[parameter].append(col)
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for parameter in parameters:
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mini_df = df[info_cols[parameter]]
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fig, ax = plt.subplots()
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ax.set_title(parameter)
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for col in info_cols[parameter]:
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ax.plot(df['iters'].values,
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df[col].values,
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label=col,
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linestyle='-',
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marker='o')
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ax.set_xlabel('iteration')
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ax.set_ylabel('Value')
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plt.legend()
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plt.show()
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fig, ax = plt.subplots()
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ax.set_title('best_obj_value')
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ax.plot(df['iters'].values,
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df['best_obj'].values,
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linestyle='-',
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marker='o')
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ax.set_xlabel('iteration')
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ax.set_ylabel('Value')
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plt.show()
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