BudakovIS/docs/data/1-st-exercize/experiment_results.csv

@@ -0,0 +1,31 @@
+Structure,Mode,Repeat,Insert (sec),Search (sec),Delete (sec)
+LinkedList,random,1,0.140358,0.007040,0.000844
+LinkedList,random,2,0.138009,0.009197,0.000413
+LinkedList,random,3,0.114717,0.009266,0.000744
+LinkedList,random,4,0.117224,0.006914,0.000531
+LinkedList,random,5,0.136302,0.010432,0.000582
+LinkedList,sorted,1,0.106921,0.007845,0.000566
+LinkedList,sorted,2,0.116404,0.015005,0.004900
+LinkedList,sorted,3,0.125122,0.006956,0.000708
+LinkedList,sorted,4,0.122401,0.004220,0.000474
+LinkedList,sorted,5,0.111422,0.008343,0.000551
+HashTable,random,1,0.025442,0.004652,0.000078
+HashTable,random,2,0.035477,0.000985,0.000091
+HashTable,random,3,0.015387,0.001249,0.000298
+HashTable,random,4,0.014196,0.001167,0.000096
+HashTable,random,5,0.013819,0.000910,0.000094
+HashTable,sorted,1,0.013713,0.000897,0.000060
+HashTable,sorted,2,0.016816,0.001013,0.000116
+HashTable,sorted,3,0.018408,0.001019,0.000084
+HashTable,sorted,4,0.014490,0.000886,0.000093
+HashTable,sorted,5,0.012493,0.000867,0.000075
+BST,random,1,0.006755,0.000468,0.000065
+BST,random,2,0.006454,0.000380,0.000052
+BST,random,3,0.003348,0.000266,0.000033
+BST,random,4,0.004785,0.000379,0.000053
+BST,random,5,0.005253,0.000438,0.000083
+BST,sorted,1,0.331066,0.028260,0.002915
+BST,sorted,2,0.342009,0.025769,0.003155
+BST,sorted,3,0.282425,0.031293,0.002984
+BST,sorted,4,0.313816,0.022712,0.002957
+BST,sorted,5,0.287008,0.032645,0.002415

BudakovIS/docs/data/1-st-exercize/plot_results.py

@@ -0,0 +1,44 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+
+# Загрузка данных
+df = pd.read_csv('experiment_results.csv')
+
+# Усреднение по повторам
+mean_times = df.groupby(['Structure', 'Mode'])[['Insert (sec)', 'Search (sec)', 'Delete (sec)']].mean().reset_index()
+
+# Подготовка данных для графиков
+structures = mean_times['Structure'].unique()
+modes = mean_times['Mode'].unique()
+
+# Создание трех графиков (вставка, поиск, удаление)
+fig, axes = plt.subplots(1, 3, figsize=(15, 5))
+
+operations = ['Insert (sec)', 'Search (sec)', 'Delete (sec)']
+titles = ['Вставка', 'Поиск', 'Удаление']
+
+for ax, op, title in zip(axes, operations, titles):
+    # Для каждой структуры строим две колонки (random, sorted)
+    x = np.arange(len(structures))
+    width = 0.35
+    
+    random_vals = []
+    sorted_vals = []
+    for s in structures:
+        random_row = mean_times[(mean_times['Structure']==s) & (mean_times['Mode']=='random')]
+        sorted_row = mean_times[(mean_times['Structure']==s) & (mean_times['Mode']=='sorted')]
+        random_vals.append(random_row[op].values[0] if not random_row.empty else 0)
+        sorted_vals.append(sorted_row[op].values[0] if not sorted_row.empty else 0)
+    
+    ax.bar(x - width/2, random_vals, width, label='Случайный')
+    ax.bar(x + width/2, sorted_vals, width, label='Отсортированный')
+    ax.set_xticks(x)
+    ax.set_xticklabels(structures)
+    ax.set_ylabel('Время (сек)')
+    ax.set_title(title)
+    ax.legend()
+
+plt.tight_layout()
+plt.savefig('../../performance_comparison.png', dpi=150)
+plt.show()

BudakovIS/docs/data/experiment_results.csv

@@ -1,31 +0,0 @@
-Structure,Mode,Repeat,Insert (sec),Search (sec),Delete (sec)
-LinkedList,random,1,0.110077,0.006972,0.000836
-LinkedList,random,2,0.105159,0.008245,0.000690
-LinkedList,random,3,0.111559,0.008142,0.000632
-LinkedList,random,4,0.116443,0.007497,0.000519
-LinkedList,random,5,0.128044,0.007971,0.000584
-LinkedList,sorted,1,0.098338,0.007254,0.000515
-LinkedList,sorted,2,0.101167,0.004475,0.000742
-LinkedList,sorted,3,0.128987,0.007993,0.000649
-LinkedList,sorted,4,0.104280,0.006707,0.000676
-LinkedList,sorted,5,0.129192,0.007550,0.000669
-HashTable,random,1,0.014989,0.001023,0.000067
-HashTable,random,2,0.010627,0.000918,0.000083
-HashTable,random,3,0.012970,0.001416,0.000090
-HashTable,random,4,0.013139,0.001172,0.000092
-HashTable,random,5,0.013617,0.000928,0.000091
-HashTable,sorted,1,0.016275,0.000988,0.000099
-HashTable,sorted,2,0.017436,0.000888,0.000094
-HashTable,sorted,3,0.017177,0.000977,0.000080
-HashTable,sorted,4,0.013340,0.001643,0.000248
-HashTable,sorted,5,0.013750,0.001013,0.000176
-BST,random,1,0.006446,0.000436,0.000073
-BST,random,2,0.005296,0.000442,0.000070
-BST,random,3,0.006276,0.000486,0.000055
-BST,random,4,0.004277,0.000230,0.000033
-BST,random,5,0.004287,0.000230,0.000034
-BST,sorted,1,0.286207,0.021908,0.002439
-BST,sorted,2,0.275166,0.024806,0.003805
-BST,sorted,3,0.334667,0.020466,0.002237
-BST,sorted,4,0.319684,0.019011,0.002984
-BST,sorted,5,0.299339,0.028599,0.001916