KuzminskiyAA/Task 1/Dogs/Data/1.py

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+import time
+import random
+import csv
+import matplotlib.pyplot as plt
+import numpy as np
+
+def ll_insert(head, name, phone):
+    new_node = {'name': name, 'phone': phone, 'next': None}
+    if head is None:
+        return new_node
+    current = head
+    while current:
+        if current['name'] == name:
+            current['phone'] = phone
+            return head
+        if current['next'] is None:
+            current['next'] = new_node
+            return head
+        current = current['next']
+    return head
+
+def ll_find(head, name):
+    current = head
+    while current:
+        if current['name'] == name:
+            return current['phone']
+        current = current['next']
+    return None
+
+def ll_delete(head, name):
+    if head is None:
+        return None
+    if head['name'] == name:
+        return head['next']
+    current = head
+    while current['next']:
+        if current['next']['name'] == name:
+            current['next'] = current['next']['next']
+            return head
+        current = current['next']
+    return head
+
+def ll_list_all(head):
+    records = []
+    current = head
+    while current:
+        records.append((current['name'], current['phone']))
+        current = current['next']
+    return sorted(records, key=lambda x: x[0])
+def hash_func(name, size):
+    return sum(ord(c) for c in name) % size
+
+def ht_create(size=1000):
+    return [None] * size
+
+def ht_insert(table, name, phone):
+    idx = hash_func(name, len(table))
+    table[idx] = ll_insert(table[idx], name, phone)
+
+def ht_find(table, name):
+    idx = hash_func(name, len(table))
+    return ll_find(table[idx], name)
+
+def ht_delete(table, name):
+    idx = hash_func(name, len(table))
+    table[idx] = ll_delete(table[idx], name)
+
+def ht_list_all(table):
+    records = []
+    for bucket in table:
+        current = bucket
+        while current:
+            records.append((current['name'], current['phone']))
+            current = current['next']
+    return sorted(records, key=lambda x: x[0])
+def bst_insert(root, name, phone):
+    if root is None:
+        return {'name': name, 'phone': phone, 'left': None, 'right': None}
+    if name < root['name']:
+        root['left'] = bst_insert(root['left'], name, phone)
+    elif name > root['name']:
+        root['right'] = bst_insert(root['right'], name, phone)
+    else:
+        root['phone'] = phone
+    return root
+
+def bst_find(root, name):
+    if root is None:
+        return None
+    if name == root['name']:
+        return root['phone']
+    elif name < root['name']:
+        return bst_find(root['left'], name)
+    else:
+        return bst_find(root['right'], name)
+
+def bst_min(node):
+    while node and node['left']:
+        node = node['left']
+    return node
+
+def bst_delete(root, name):
+    if root is None:
+        return None
+    if name < root['name']:
+        root['left'] = bst_delete(root['left'], name)
+    elif name > root['name']:
+        root['right'] = bst_delete(root['right'], name)
+    else:
+        if root['left'] is None:
+            return root['right']
+        if root['right'] is None:
+            return root['left']
+        min_node = bst_min(root['right'])
+        root['name'] = min_node['name']
+        root['phone'] = min_node['phone']
+        root['right'] = bst_delete(root['right'], min_node['name'])
+    return root
+
+def bst_list_all(root):
+    records = []
+    if root:
+        records.extend(bst_list_all(root['left']))
+        records.append((root['name'], root['phone']))
+        records.extend(bst_list_all(root['right']))
+    return records
+def generate_data(n=2000):
+    random_data = [(f"User_{i:05d}", str(i)) for i in range(n)]
+    random.shuffle(random_data)
+    sorted_data = sorted(random_data, key=lambda x: x[0])
+    return random_data, sorted_data
+def run_test(data, struct_name, create, insert, find, delete):
+    times = {'insert': [], 'search': [], 'delete': []}
+    
+    for _ in range(5):
+        s = create()
+        
+        start = time.perf_counter()
+        if struct_name == 'LinkedList' or struct_name == 'BST':
+            for name, phone in data:
+                s = insert(s, name, phone)
+        else:
+            for name, phone in data:
+                insert(s, name, phone)
+        times['insert'].append(time.perf_counter() - start)
+        
+        names = [random.choice(data)[0] for _ in range(100)] + [f"None_{i}" for i in range(10)]
+        start = time.perf_counter()
+        for name in names:
+            find(s, name)
+        times['search'].append(time.perf_counter() - start)
+        
+        del_names = [random.choice(data)[0] for _ in range(50)]
+        start = time.perf_counter()
+        for name in del_names:
+            if struct_name == 'LinkedList' or struct_name == 'BST':
+                s = delete(s, name)
+            else:
+                delete(s, name)
+        times['delete'].append(time.perf_counter() - start)
+    
+    return {op: sum(t)/len(t) for op, t in times.items()}
+def plot_results(data_matrix):
+    structures = ['LinkedList', 'HashTable', 'BST']
+    operations = ['insert', 'search', 'delete']
+    modes = ['random', 'sorted']
+    
+    fig, axes = plt.subplots(2, 2, figsize=(14, 12))
+    
+    x = np.arange(len(structures))
+    width = 0.25
+    
+    for i, op in enumerate(operations):
+        values = [data_matrix[s]['random'][op] for s in structures]
+        axes[0,0].bar(x + i*width, values, width, label=op)
+    axes[0,0].set_xlabel('Структура данных')
+    axes[0,0].set_ylabel('Время (секунды)')
+    axes[0,0].set_title('Случайный порядок данных')
+    axes[0,0].set_xticks(x + width, structures)
+    axes[0,0].legend()
+    axes[0,0].grid(True, alpha=0.3)
+    
+    for i, op in enumerate(operations):
+        values = [data_matrix[s]['sorted'][op] for s in structures]
+        axes[0,1].bar(x + i*width, values, width, label=op)
+    axes[0,1].set_xlabel('Структура данных')
+    axes[0,1].set_ylabel('Время (секунды)')
+    axes[0,1].set_title('Отсортированный порядок данных')
+    axes[0,1].set_xticks(x + width, structures)
+    axes[0,1].legend()
+    axes[0,1].grid(True, alpha=0.3)
+    
+    x = np.arange(len(operations))
+    width = 0.35
+    for i, mode in enumerate(modes):
+        values = [data_matrix['BST'][mode][op] for op in operations]
+        axes[1,0].bar(x + i*width, values, width, label=mode)
+    axes[1,0].set_xlabel('Операция')
+    axes[1,0].set_ylabel('Время (секунды)')
+    axes[1,0].set_title('BST: влияние порядка данных')
+    axes[1,0].set_xticks(x + width/2, operations)
+    axes[1,0].legend()
+    axes[1,0].grid(True, alpha=0.3)
+    
+    for struct in structures:
+        times_random = [data_matrix[struct]['random'][op] for op in operations]
+        times_sorted = [data_matrix[struct]['sorted'][op] for op in operations]
+        axes[1,1].plot(operations, times_random, marker='o', label=f'{struct} случайный')
+        axes[1,1].plot(operations, times_sorted, marker='s', linestyle='--', label=f'{struct} отсортированный')
+    axes[1,1].set_yscale('log')
+    axes[1,1].set_xlabel('Операция')
+    axes[1,1].set_ylabel('Время (секунды) - логарифмическая шкала')
+    axes[1,1].set_title('Сравнение производительности')
+    axes[1,1].legend()
+    axes[1,1].grid(True, alpha=0.3)
+    
+    plt.tight_layout()
+    plt.savefig('performance_graphs.png')
+    plt.show()
+random_data, sorted_data = generate_data(2000)
+
+structs = [
+    ('LinkedList', lambda: None, ll_insert, ll_find, ll_delete),
+    ('HashTable', lambda: ht_create(2000), ht_insert, ht_find, ht_delete),
+    ('BST', lambda: None, bst_insert, bst_find, bst_delete)
+]
+
+data_matrix = {'LinkedList': {'random': {}, 'sorted': {}},
+               'HashTable': {'random': {}, 'sorted': {}},
+               'BST': {'random': {}, 'sorted': {}}}
+
+for name, create, insert, find, delete in structs:
+    for order, data in [('random', random_data), ('sorted', sorted_data)]:
+        times = run_test(data, name, create, insert, find, delete)
+        data_matrix[name][order] = times
+
+with open('results.csv', 'w', newline='') as f:
+    writer = csv.writer(f)
+    writer.writerow(['структура', 'порядок_данных', 'операция', 'время_секунды'])
+    for name in ['LinkedList', 'HashTable', 'BST']:
+        for order in ['random', 'sorted']:
+            for op in ['insert', 'search', 'delete']:
+                writer.writerow([name, order, op, data_matrix[name][order][op]])
+
+plot_results(data_matrix)
+
+print("\n РЕЗУЛЬТАТЫ")
+for name in ['LinkedList', 'HashTable', 'BST']:
+    for order in ['random', 'sorted']:
+        print(f"{name} {order}: вставка={data_matrix[name][order]['insert']:.6f}, поиск={data_matrix[name][order]['search']:.6f}, удаление={data_matrix[name][order]['delete']:.6f}")

KuzminskiyAA/Task 1/Dogs/Data/results.csv

@@ -0,0 +1,19 @@
+структура,порядок_данных,операция,время_секунды
+LinkedList,random,insert,0.4430991000015638
+LinkedList,random,search,0.019253799998841713
+LinkedList,random,delete,0.012056579999625682
+LinkedList,sorted,insert,0.4242827600013698
+LinkedList,sorted,search,0.019056700001237915
+LinkedList,sorted,delete,0.010539219998463523
+HashTable,random,insert,0.025478639999346343
+HashTable,random,search,0.0009841200007940643
+HashTable,random,delete,0.0006616600003326312
+HashTable,sorted,insert,0.025232040000264532
+HashTable,sorted,search,0.0010681599989766255
+HashTable,sorted,delete,0.0006402399987564423
+BST,random,insert,0.004588020002120175
+BST,random,search,0.00022194000048330053
+BST,random,delete,0.00013212000048952178
+BST,sorted,insert,0.660595199999807
+BST,sorted,search,0.025651479998487048
+BST,sorted,delete,0.015685519999533427