forked from UNN/2026-rff_mp
129 lines
4.7 KiB
Python
129 lines
4.7 KiB
Python
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import csv
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import os
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try:
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import matplotlib.pyplot as plt
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import matplotlib.patches as mpatches
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HAS_MPL = True
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except ImportError:
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HAS_MPL = False
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print("⚠️ matplotlib не установлен. Установите: pip install matplotlib")
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print(" Графики будут пропущены, таблица результатов выведена в терминал.\n")
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CSV_PATH = os.path.join(os.path.dirname(__file__), 'results.csv')
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PLOTS_DIR = os.path.dirname(__file__)
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def load_results(path):
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data = {}
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with open(path, newline='', encoding='utf-8') as f:
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reader = csv.reader(f)
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header = next(reader)
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for row in reader:
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struct, mode, op = row[0], row[1], row[2]
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mean = float(row[3])
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data[(struct, mode, op)] = mean
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return data
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STRUCTS = ["LinkedList", "HashTable", "BST"]
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MODES = ["случайный", "сортированный"]
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OPS = ["insert", "find", "delete"]
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COLORS = {"LinkedList": "#4E9AF1", "HashTable": "#F4845F", "BST": "#6BCB77"}
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def plot_by_operation(data):
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fig, axes = plt.subplots(1, 3, figsize=(15, 5))
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fig.suptitle("Сравнение структур данных\n(телефонный справочник, N=10 000)",
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fontsize=14, fontweight='bold')
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for ax, op in zip(axes, OPS):
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x_labels = []
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values = []
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colors = []
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for mode in MODES:
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for struct in STRUCTS:
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key = (struct, mode, op)
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val = data.get(key, 0)
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x_labels.append(f"{struct}\n({mode[:4]})")
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values.append(val)
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colors.append(COLORS[struct])
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bars = ax.bar(range(len(values)), values, color=colors,
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edgecolor='white', linewidth=0.8)
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ax.set_xticks(range(len(x_labels)))
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ax.set_xticklabels(x_labels, fontsize=8, rotation=15, ha='right')
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ax.set_ylabel("Время (с)", fontsize=9)
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ax.set_title(f"Операция: {op}", fontweight='bold')
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ax.grid(axis='y', alpha=0.3)
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for bar, val in zip(bars, values):
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ax.text(bar.get_x() + bar.get_width() / 2,
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bar.get_height() + max(values) * 0.01,
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f"{val:.4f}",
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ha='center', va='bottom', fontsize=7)
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patches = [mpatches.Patch(color=c, label=s) for s, c in COLORS.items()]
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fig.legend(handles=patches, loc='lower center', ncol=3,
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bbox_to_anchor=(0.5, -0.05))
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plt.tight_layout()
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out_path = os.path.join(PLOTS_DIR, 'comparison_by_operation.png')
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plt.savefig(out_path, dpi=150, bbox_inches='tight')
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print(f"✅ График сохранён: {out_path}")
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plt.show()
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def plot_sorted_vs_random(data):
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fig, axes = plt.subplots(1, 3, figsize=(14, 5))
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fig.suptitle("Влияние порядка данных на время операций",
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fontsize=13, fontweight='bold')
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for ax, struct in zip(axes, STRUCTS):
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rand_vals = [data.get((struct, "случайный", op), 0) for op in OPS]
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sort_vals = [data.get((struct, "сортированный", op), 0) for op in OPS]
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x = range(len(OPS))
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w = 0.35
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bars1 = ax.bar([i - w/2 for i in x], rand_vals, width=w,
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label="случайный", color="#4E9AF1", edgecolor='white')
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bars2 = ax.bar([i + w/2 for i in x], sort_vals, width=w,
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label="сортированный", color="#F4845F", edgecolor='white')
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ax.set_xticks(list(x))
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ax.set_xticklabels(OPS)
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ax.set_title(struct, fontweight='bold')
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ax.set_ylabel("Время (с)", fontsize=9)
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ax.legend(fontsize=8)
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ax.grid(axis='y', alpha=0.3)
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plt.tight_layout()
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out_path = os.path.join(PLOTS_DIR, 'sorted_vs_random.png')
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plt.savefig(out_path, dpi=150, bbox_inches='tight')
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print(f"✅ График сохранён: {out_path}")
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plt.show()
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def print_table(data):
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print(f"\n{'Структура':<12} {'Режим':<16} {'Операция':<10} {'Время (с)':<12}")
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print("-" * 52)
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for (struct, mode, op), mean in sorted(data.items()):
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print(f"{struct:<12} {mode:<16} {op:<10} {mean:.6f}")
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if __name__ == "__main__":
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if not os.path.exists(CSV_PATH):
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print(f"❌ Файл результатов не найден: {CSV_PATH}")
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print(" Сначала запустите: python benchmark.py")
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exit(1)
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data = load_results(CSV_PATH)
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print_table(data)
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if HAS_MPL:
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plot_by_operation(data)
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plot_sorted_vs_random(data)
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else:
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print("\n💡 Установите matplotlib для графиков:")
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print(" pip install matplotlib")
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