forked from UNN/2026-rff_mp
39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
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import pandas as pd
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import matplotlib.pyplot as plt
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import numpy as np
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df = pd.read_csv('experiment_results.csv')
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mean_times = df.groupby(['Structure', 'Mode'])[['Insert (sec)', 'Search (sec)', 'Delete (sec)']].mean().reset_index()
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structures = mean_times['Structure'].unique()
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modes = mean_times['Mode'].unique()
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fig, axes = plt.subplots(1, 3, figsize=(15, 5))
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operations = ['Insert (sec)', 'Search (sec)', 'Delete (sec)']
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titles = ['Insertion', 'Search', 'Deletion']
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for ax, op, title in zip(axes, operations, titles):
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x = np.arange(len(structures))
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width = 0.35
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random_vals = []
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sorted_vals = []
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for s in structures:
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random_row = mean_times[(mean_times['Structure'] == s) & (mean_times['Mode'] == 'random')]
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sorted_row = mean_times[(mean_times['Structure'] == s) & (mean_times['Mode'] == 'sorted')]
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random_vals.append(random_row[op].values[0] if not random_row.empty else 0)
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sorted_vals.append(sorted_row[op].values[0] if not sorted_row.empty else 0)
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ax.bar(x - width/2, random_vals, width, label='Random')
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ax.bar(x + width/2, sorted_vals, width, label='Sorted')
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ax.set_xticks(x)
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ax.set_xticklabels(structures)
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ax.set_ylabel('Time (seconds)')
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ax.set_title(title)
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ax.legend()
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plt.tight_layout()
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plt.savefig('performance_comparison.png', dpi=150)
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plt.show()
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