[1] добавлены графики

shalovsa/lab1/docs/data/plot_results.py

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

shalovsa/lab1/docs/data/results.csv

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+Структура,Режим,Операция,Среднее (с),Замер_1,Замер_2,Замер_3,Замер_4,Замер_5
+LinkedList,случайный,insert,2.013381,2.030341,1.985393,2.000117,2.000130,2.050923
+LinkedList,случайный,find,0.026258,0.026263,0.027186,0.026271,0.026350,0.025217
+LinkedList,случайный,delete,0.015552,0.017207,0.014387,0.015304,0.015317,0.015547
+HashTable,случайный,insert,0.014448,0.014376,0.014608,0.015115,0.013931,0.014212
+HashTable,случайный,find,0.000161,0.000162,0.000161,0.000161,0.000158,0.000161
+HashTable,случайный,delete,0.000088,0.000089,0.000089,0.000088,0.000086,0.000086
+BST,случайный,insert,0.015575,0.015822,0.015653,0.015507,0.015398,0.015496
+BST,случайный,find,0.000133,0.000135,0.000133,0.000131,0.000133,0.000133
+BST,случайный,delete,0.000100,0.000104,0.000100,0.000100,0.000099,0.000099
+LinkedList,сортированный,insert,1.890415,1.937600,1.916341,1.863388,1.872563,1.862181
+LinkedList,сортированный,find,0.023136,0.030373,0.021794,0.021670,0.020861,0.020980
+LinkedList,сортированный,delete,0.014986,0.017694,0.014155,0.014365,0.014293,0.014424
+HashTable,сортированный,insert,0.017723,0.015734,0.019191,0.019721,0.015843,0.018128
+HashTable,сортированный,find,0.000223,0.000263,0.000206,0.000226,0.000154,0.000264
+HashTable,сортированный,delete,0.000125,0.000144,0.000112,0.000132,0.000094,0.000141
+BST,сортированный,insert,3.535999,3.577140,3.570114,3.581931,3.485064,3.465746
+BST,сортированный,find,0.030666,0.030318,0.033654,0.030108,0.029537,0.029713
+BST,сортированный,delete,0.038312,0.037349,0.040109,0.037735,0.036555,0.039810