33 lines
884 B
Python
33 lines
884 B
Python
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# read a csv of two columns and plot them in 2d with seaborn
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import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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from config import CONDITIONING_RESULTS, PLOTS_PATH
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def plot_conditioning():
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df = pd.read_csv(CONDITIONING_RESULTS.format('conditioning.csv'))
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sns.set(style="whitegrid")
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sns.set_context('paper')
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plt.figure(figsize=(11, 8))
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sns.lineplot(data=df, x='lambda', y='condnum', marker='o')
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plt.xticks(fontsize=15)
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plt.yticks(fontsize=15)
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plt.xlabel('λ', fontsize=20)
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plt.ylabel('k(X^)', fontsize=20)
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plt.xscale('log')
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plt.yscale('log')
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plt.title('Condition number of X^ with respect to λ', fontsize=25, pad=20, fontweight='bold')
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plt.savefig(PLOTS_PATH.format('conditioning', 'conditioning.png'), bbox_inches='tight', dpi=100)
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plt.show()
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if __name__ == '__main__':
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plot_conditioning()
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