forked from UNN/2026-rff_mp
312 lines
12 KiB
Python
312 lines
12 KiB
Python
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import csv
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import random
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import sys
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import time
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import threading
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import matplotlib.pyplot as plt
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sys.setrecursionlimit(30000)
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threading.stack_size(64*1024*1024)
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def ll_insert(head, name, phone):
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"""Добавляет запись или обновляет телефон, если имя уже существует. Возвращает новую голову списка."""
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current = head
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while current is not None:
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if current["name"] == name:
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current["phone"] = phone
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return head
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current = current["next"]
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fresh_node = {"name": name, "phone": phone, "next": head}
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return fresh_node
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def ll_find(head, name):
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"""Ищет узел по имени. Возвращает телефон или None."""
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current = head
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while current is not None:
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if current["name"] == name:
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return current["phone"]
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current = current["next"]
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return None
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def ll_delete(head, name):
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"""Удаляет узел по имени. Возвращает новую голову списка."""
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current = head
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previous = None
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while current is not None:
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if current["name"] == name:
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if previous is None:
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return current["next"]
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else:
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previous["next"] = current["next"]
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return head
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previous = current
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current = current["next"]
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return head
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def ll_list_all(head):
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"""Собирает все записи в список и сортирует их по имени."""
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entries = []
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current = head
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while current is not None:
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entries.append((current["name"], current["phone"]))
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current = current["next"]
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entries.sort(key=lambda item: item[0])
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return entries
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def ht_create(size=1000):
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"""Создает пустую хеш-таблицу заданного размера."""
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return [None] * size
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def ht_insert(buckets, name, phone):
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"""Вычисляет индекс бакета и вызывает ll_insert."""
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bucket_idx = abs(hash(name)) % len(buckets)
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buckets[bucket_idx] = ll_insert(buckets[bucket_idx], name, phone)
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def ht_find(buckets, name):
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"""Вычисляет индекс бакета и вызывает ll_find."""
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bucket_idx = abs(hash(name)) % len(buckets)
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return ll_find(buckets[bucket_idx], name)
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def ht_delete(buckets, name):
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"""Вычисляет индекс бакета и вызывает ll_delete."""
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bucket_idx = abs(hash(name)) % len(buckets)
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buckets[bucket_idx] = ll_delete(buckets[bucket_idx], name)
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def ht_list_all(buckets):
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"""Собирает записи из всех бакетов и сортирует их по имени."""
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entries = []
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for head_node in buckets:
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current = head_node
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while current is not None:
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entries.append((current["name"], current["phone"]))
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current = current["next"]
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entries.sort(key=lambda item: item[0])
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return entries
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def bst_insert(root, name, phone):
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"""Рекурсивно вставляет узел или обновляет телефон."""
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if root is None:
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return {"name": name, "phone": phone, "left": None, "right": None}
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if name == root["name"]:
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root["phone"] = phone
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elif name < root["name"]:
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root["left"] = bst_insert(root["left"], name, phone)
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else:
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root["right"] = bst_insert(root["right"], name, phone)
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return root
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def bst_find(root, name):
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"""Рекурсивный поиск по дереву."""
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if root is None:
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return None
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if name == root["name"]:
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return root["phone"]
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elif name < root["name"]:
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return bst_find(root["left"], name)
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else:
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return bst_find(root["right"], name)
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def bst_delete(root, name):
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"""Рекурсивное удаление узла из BST."""
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if root is None:
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return None
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if name < root["name"]:
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root["left"] = bst_delete(root["left"], name)
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elif name > root["name"]:
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root["right"] = bst_delete(root["right"], name)
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else:
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if root["left"] is None:
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return root["right"]
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if root["right"] is None:
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return root["left"]
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successor = root["right"]
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while successor["left"] is not None:
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successor = successor["left"]
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root["name"] = successor["name"]
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root["phone"] = successor["phone"]
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root["right"] = bst_delete(root["right"], successor["name"])
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return root
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def bst_list_all(root):
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"""Центрированный обход дерева для сбора записей."""
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entries = []
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def _inorder(node):
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if node is not None:
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_inorder(node["left"])
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entries.append((node["name"], node["phone"]))
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_inorder(node["right"])
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_inorder(root)
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return entries
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def perform_benchmark():
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total_records = 10000
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random.seed(42)
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ordered_records = [(f"User_{i:05d}", f"8-999-123-{i:04d}") for i in range(total_records)]
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shuffled_records = ordered_records.copy()
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random.shuffle(shuffled_records)
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existing_searches = [random.choice(ordered_records)[0] for _ in range(100)]
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non_existing_searches = [f"None_{i}" for i in range(10)]
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search_queries = existing_searches + non_existing_searches
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deletion_targets = [random.choice(ordered_records)[0] for _ in range(50)]
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output_rows = [["Structure", "Mode", "Operation", "Time (sec)"]]
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graph_entries = []
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def execute_trial(structure_kind, data_mode, data_collection):
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print(f"Starting: {structure_kind} | Mode: {data_mode}...")
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insertion_measurements, search_measurements, deletion_measurements = [], [], []
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for trial_num in range(1, 6):
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if structure_kind == "LinkedList": container = None
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elif structure_kind == "HashTable": container = ht_create(size=1000)
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elif structure_kind == "BST": container = None
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# А. Вставка
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timer_start = time.perf_counter()
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if structure_kind == "LinkedList":
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for name, phone in data_collection: container = ll_insert(container, name, phone)
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elif structure_kind == "HashTable":
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for name, phone in data_collection: ht_insert(container, name, phone)
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elif structure_kind == "BST":
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for name, phone in data_collection: container = bst_insert(container, name, phone)
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insert_elapsed = time.perf_counter() - timer_start
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insertion_measurements.append(insert_elapsed)
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output_rows.append([structure_kind, data_mode, f"insert (trial {trial_num})", f"{insert_elapsed:.6f}"])
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# Б. Поиск
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timer_start = time.perf_counter()
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if structure_kind == "LinkedList":
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for name in search_queries: ll_find(container, name)
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elif structure_kind == "HashTable":
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for name in search_queries: ht_find(container, name)
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elif structure_kind == "BST":
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for name in search_queries: bst_find(container, name)
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search_elapsed = time.perf_counter() - timer_start
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search_measurements.append(search_elapsed)
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output_rows.append([structure_kind, data_mode, f"find (trial {trial_num})", f"{search_elapsed:.6f}"])
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# В. Удаление
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timer_start = time.perf_counter()
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if structure_kind == "LinkedList":
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for name in deletion_targets: container = ll_delete(container, name)
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elif structure_kind == "HashTable":
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for name in deletion_targets: ht_delete(container, name)
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elif structure_kind == "BST":
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for name in deletion_targets: container = bst_delete(container, name)
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delete_elapsed = time.perf_counter() - timer_start
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deletion_measurements.append(delete_elapsed)
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output_rows.append([structure_kind, data_mode, f"delete (trial {trial_num})", f"{delete_elapsed:.6f}"])
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# Запись средних значений
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output_rows.append([structure_kind, data_mode, "Insert (avg)", f"{sum(insertion_measurements)/5:.6f}"])
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output_rows.append([structure_kind, data_mode, "Find (avg)", f"{sum(search_measurements)/5:.6f}"])
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output_rows.append([structure_kind, data_mode, "Delete (avg)", f"{sum(deletion_measurements)/5:.6f}"])
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avg_insertion = sum(insertion_measurements) / 5
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avg_search = sum(search_measurements) / 5
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avg_deletion = sum(deletion_measurements) / 5
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graph_entries.append((structure_kind, data_mode, avg_insertion, avg_search, avg_deletion))
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# Запуск всех тестов
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execute_trial("LinkedList", "random", shuffled_records)
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execute_trial("LinkedList", "sorted", ordered_records)
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execute_trial("HashTable", "random", shuffled_records)
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execute_trial("HashTable", "sorted", ordered_records)
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execute_trial("BST", "random", shuffled_records)
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execute_trial("BST", "sorted", ordered_records)
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# Сохранение в CSV
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with open("benchmark_output.csv", "w", newline="", encoding="utf-8") as csv_file:
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csv_writer = csv.writer(csv_file)
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csv_writer.writerows(output_rows)
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print("\n[Success] All benchmarks completed! Results saved to 'benchmark_output.csv'.")
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# ВЫЗЫВАЕМ ФУНКЦИЮ ДЛЯ СОЗДАНИЯ ГРАФИКОВ
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generate_performance_charts(graph_entries)
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def generate_performance_charts(plot_data):
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"""
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Создает графики производительности структур данных.
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Args:
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plot_data: список кортежей (structure, mode, avg_insert, avg_find, avg_delete)
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"""
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if not plot_data:
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print("Нет данных для построения графиков")
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return
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# Подготовка данных
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structures = ['LinkedList', 'HashTable', 'BST']
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modes = ['random', 'sorted']
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operations = ['Insert', 'Find', 'Delete']
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# Создаем фигуру с тремя подграфиками
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fig, axes = plt.subplots(1, 3, figsize=(15, 5))
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for idx, operation in enumerate(operations):
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ax = axes[idx]
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# Данные для текущей операции
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x_positions = []
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y_values = []
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labels = []
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for structure in structures:
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for mode in modes:
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# Находим данные для этой комбинации
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for data in plot_data:
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if data[0] == structure and data[1] == mode:
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value = data[2 + idx] # 2=insert, 3=find, 4=delete
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x_positions.append(len(x_positions))
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y_values.append(value)
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labels.append(f"{structure}\n{mode}")
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# Создаем столбчатую диаграмму
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bars = ax.bar(x_positions, y_values, color=['skyblue', 'lightcoral']*3)
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# Настройка графика
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ax.set_title(f'Операция: {operation}', fontsize=14, fontweight='bold')
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ax.set_ylabel('Время (сек)', fontsize=12)
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ax.set_xticks(x_positions)
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ax.set_xticklabels(labels, rotation=45, ha='right', fontsize=10)
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ax.grid(axis='y', alpha=0.3)
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# Добавляем значения над столбцами
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for bar, value in zip(bars, y_values):
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ax.text(bar.get_x() + bar.get_width()/2, bar.get_height(),
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f'{value:.4f}', ha='center', va='bottom', fontsize=8)
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plt.tight_layout()
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plt.savefig('performance_charts.png', dpi=300, bbox_inches='tight')
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plt.show()
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print("Графики сохранены в 'performance_charts.png'")
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if __name__ == '__main__':
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benchmark_thread = threading.Thread(target=perform_benchmark)
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benchmark_thread.start()
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benchmark_thread.join()
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# Дополнительно: если графики не показались автоматически
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# Можно вызвать функцию напрямую после завершения потока
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print("\nПрограмма завершена. Проверьте файл 'performance_charts.png'")
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