160 lines
6.7 KiB
Python
160 lines
6.7 KiB
Python
import matplotlib.pyplot as plt
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import csv
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import numpy as np
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import os
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plt.rcParams['font.size'] = 10
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plt.rcParams['font.family'] = 'sans-serif'
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def plot_results(csv_file="docs/data/results.csv"):
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if not os.path.exists(csv_file):
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print(f"Файл {csv_file} не найден. Сначала запустите benchmark.py")
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return
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data = {}
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with open(csv_file, 'r', encoding='utf-8') as f:
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reader = csv.reader(f)
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next(reader)
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for row in reader:
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if len(row) < 5:
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continue
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struct, mode, op, _, time_val = row
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try:
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time_val = float(time_val)
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except:
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continue
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if struct not in data:
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data[struct] = {}
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if mode not in data[struct]:
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data[struct][mode] = {}
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if op not in data[struct][mode]:
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data[struct][mode][op] = []
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data[struct][mode][op].append(time_val)
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operations = ['вставка', 'поиск', 'удаление']
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op_names = ['Вставка', 'Поиск', 'Удаление']
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structures = ['LinkedList', 'HashTable', 'BST']
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modes = ['случайный', 'отсортированный']
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colors = {'LinkedList': '#3498db', 'HashTable': '#2ecc71', 'BST': '#e74c3c'}
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fig, axes = plt.subplots(1, 3, figsize=(14, 5))
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fig.suptitle('Сравнение производительности структур данных\n(500 записей, 3 повторения)', fontsize=14, fontweight='bold')
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for idx, (op, op_name) in enumerate(zip(operations, op_names)):
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ax = axes[idx]
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x_positions = []
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labels = []
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values = []
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errors = []
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colors_list = []
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position = 0
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for struct in structures:
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for mode in modes:
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if struct in data and mode in data[struct] and op in data[struct][mode]:
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times = data[struct][mode][op]
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if times:
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avg_time = np.mean(times)
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std_time = np.std(times) if len(times) > 1 else 0
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x_positions.append(position)
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labels.append(f'{struct}\n({mode[:4]})')
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values.append(avg_time)
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errors.append(std_time)
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colors_list.append(colors[struct])
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position += 1
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bars = ax.bar(x_positions, values, yerr=errors, capsize=5, color=colors_list, alpha=0.8, edgecolor='black', linewidth=0.5)
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ax.set_xticks(x_positions)
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ax.set_xticklabels(labels, fontsize=8, rotation=45, ha='right')
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ax.set_ylabel('Время (секунды)', fontsize=10)
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ax.set_title(f'{op_name}', fontsize=12, fontweight='bold')
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ax.grid(True, alpha=0.3, axis='y')
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for bar, val in zip(bars, values):
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if val > 0:
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height = bar.get_height()
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ax.text(bar.get_x() + bar.get_width()/2., height + max(values)*0.02,
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f'{val:.4f}', ha='center', va='bottom', fontsize=7, rotation=0)
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plt.tight_layout()
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plt.savefig('docs/data/performance_graphs.png', dpi=300, bbox_inches='tight')
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plt.show()
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fig2, ax2 = plt.subplots(figsize=(10, 6))
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fig2.suptitle('Влияние порядка данных на производительность BST', fontsize=14, fontweight='bold')
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if 'BST' in data:
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bst_data = data['BST']
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x_pos = []
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labels = []
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random_vals = []
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sorted_vals = []
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for idx, op in enumerate(operations):
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random_time = 0
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sorted_time = 0
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if 'случайный' in bst_data and op in bst_data['случайный']:
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random_time = np.mean(bst_data['случайный'][op])
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if 'отсортированный' in bst_data and op in bst_data['отсортированный']:
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sorted_time = np.mean(bst_data['отсортированный'][op])
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x_pos.append(idx)
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x_pos.append(idx + 0.35)
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labels.append(op)
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random_vals.append(random_time)
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sorted_vals.append(sorted_time)
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width = 0.35
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bars1 = ax2.bar([i - width/2 for i in range(len(operations))], random_vals, width,
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label='Случайный порядок', color='#2ecc71', alpha=0.8, edgecolor='black')
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bars2 = ax2.bar([i + width/2 for i in range(len(operations))], sorted_vals, width,
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label='Отсортированный порядок', color='#e74c3c', alpha=0.8, edgecolor='black')
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ax2.set_xticks(range(len(operations)))
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ax2.set_xticklabels(['Вставка', 'Поиск', 'Удаление'], fontsize=10)
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ax2.set_ylabel('Время (секунды)', fontsize=10)
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ax2.set_xlabel('Операция', fontsize=10)
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ax2.legend(fontsize=10)
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ax2.grid(True, alpha=0.3, axis='y')
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for bar, val in zip(bars1, random_vals):
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if val > 0:
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ax2.text(bar.get_x() + bar.get_width()/2., bar.get_height() + max(random_vals + sorted_vals)*0.02,
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f'{val:.4f}', ha='center', va='bottom', fontsize=8)
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for bar, val in zip(bars2, sorted_vals):
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if val > 0:
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ax2.text(bar.get_x() + bar.get_width()/2., bar.get_height() + max(random_vals + sorted_vals)*0.02,
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f'{val:.4f}', ha='center', va='bottom', fontsize=8)
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plt.tight_layout()
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plt.savefig('docs/data/bst_comparison.png', dpi=300, bbox_inches='tight')
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plt.show()
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print("\n" + "="*60)
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print("ИТОГОВАЯ ТАБЛИЦА РЕЗУЛЬТАТОВ")
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print("="*60)
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print(f"{'Структура':<15} {'Режим':<12} {'Вставка':<12} {'Поиск':<12} {'Удаление':<12}")
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print("-"*60)
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for struct in structures:
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for mode in modes:
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if struct in data and mode in data[struct]:
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insert_times = data[struct][mode].get('вставка', [0])
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find_times = data[struct][mode].get('поиск', [0])
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delete_times = data[struct][mode].get('удаление', [0])
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insert_avg = np.mean(insert_times) if insert_times else 0
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find_avg = np.mean(find_times) if find_times else 0
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delete_avg = np.mean(delete_times) if delete_times else 0
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print(f"{struct:<15} {mode:<12} {insert_avg:<12.6f} {find_avg:<12.6f} {delete_avg:<12.6f}")
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print("="*60)
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if __name__ == "__main__":
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plot_results() |