forked from UNN/2026-rff_mp
Merge pull request '[1] Первая лабораторная работа' (#235) from mylnikovas/2026-rff_mp:task_1 into develop
Reviewed-on: UNN/2026-rff_mp#235
This commit is contained in:
commit
6bf6bc0c5f
92
MylnikovAS/task_1/docs/data/experiment_part.py
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92
MylnikovAS/task_1/docs/data/experiment_part.py
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def main():
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N = 10000
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random.seed(42)
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records_sorted = [(f"User_{i:05d}", f"8-999-123-{i:04d}") for i in range(N)]
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records_shuffled = records_sorted.copy()
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random.shuffle(records_shuffled)
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search_existing = [random.choice(records_sorted)[0] for _ in range(100)]
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search_non_existing = [f"None_{i}" for i in range(10)]
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search_names = search_existing + search_non_existing
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delete_names = [random.choice(records_sorted)[0] for _ in range(50)]
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csv_rows = [["Structure", "Mode", "Operation", "Time (sec)"]]
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plot_data = []
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def run_experiment(struct_type, mode, dataset):
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print(f"Start: {struct_type} | Mode: {mode}...")
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times_insert, times_find, times_delete = [], [], []
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for round_idx in range(1, 6):
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if struct_type == "LinkedList": container = None
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elif struct_type == "HashTable": container = ht_create(size=1000)
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elif struct_type == "BST": container = None
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# А. Вставка
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start = time.perf_counter()
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if struct_type == "LinkedList":
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for name, phone in dataset: container = ll_insert(container, name, phone)
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elif struct_type == "HashTable":
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for name, phone in dataset: ht_insert(container, name, phone)
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elif struct_type == "BST":
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for name, phone in dataset: container = bst_insert(container, name, phone)
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t_ins = time.perf_counter() - start
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times_insert.append(t_ins)
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csv_rows.append([struct_type, mode, f"insert (number {round_idx})", f"{t_ins:.6f}"])
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# Б. Поиск
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start = time.perf_counter()
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if struct_type == "LinkedList":
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for name in search_names: ll_find(container, name)
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elif struct_type == "HashTable":
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for name in search_names: ht_find(container, name)
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elif struct_type == "BST":
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for name in search_names: bst_find(container, name)
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t_find = time.perf_counter() - start
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times_find.append(t_find)
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csv_rows.append([struct_type, mode, f"find (number {round_idx})", f"{t_find:.6f}"])
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# В. Удаление
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start = time.perf_counter()
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if struct_type == "LinkedList":
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for name in delete_names: container = ll_delete(container, name)
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elif struct_type == "HashTable":
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for name in delete_names: ht_delete(container, name)
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elif struct_type == "BST":
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for name in delete_names: container = bst_delete(container, name)
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t_del = time.perf_counter() - start
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times_delete.append(t_del)
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csv_rows.append([struct_type, mode, f"delete (number {round_idx})", f"{t_del:.6f}"])
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# Запись средних значений
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csv_rows.append([struct_type, mode, "Insert (average)", f"{sum(times_insert)/5:.6f}"])
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csv_rows.append([struct_type, mode, "Find (average)", f"{sum(times_find)/5:.6f}"])
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csv_rows.append([struct_type, mode, "Delete (average)", f"{sum(times_delete)/5:.6f}"])
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avg_ins = sum(times_insert) / 5
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avg_find = sum(times_find) / 5
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avg_del = sum(times_delete) / 5
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plot_data.append((struct_type, mode, avg_ins, avg_find, avg_del))
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# Запуск всех тестов
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run_experiment("LinkedList", "random", records_shuffled)
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run_experiment("LinkedList", "sorted", records_sorted)
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run_experiment("HashTable", "random", records_shuffled)
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run_experiment("HashTable", "sorted", records_sorted)
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run_experiment("BST", "random", records_shuffled)
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run_experiment("BST", "sorted", records_sorted)
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# Сохранение в CSV
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with open("results.csv", "w", newline="", encoding="utf-8") as f:
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writer = csv.writer(f)
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writer.writerows(csv_rows)
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print("\n[Успех] Все тесты завершены! Результаты сохранены в 'results.csv'.")
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generate_performance_charts(plot_data)
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if __name__ == '__main__':
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experiment_thread = threading.Thread(target=main)
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experiment_thread.start()
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experiment_thread.join()
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153
MylnikovAS/task_1/docs/data/ll_ht_bst.py
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153
MylnikovAS/task_1/docs/data/ll_ht_bst.py
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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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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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curr = head
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while curr is not None:
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if curr["name"] == name:
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curr["phone"] = phone
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return head
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curr = curr["next"]
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new_node = {"name": name, "phone": phone, "next": head}
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return new_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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curr = head
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while curr is not None:
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if curr["name"] == name:
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return curr["phone"]
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curr = curr["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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curr = head
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prev = None
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while curr is not None:
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if curr["name"] == name:
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if prev is None:
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return curr["next"]
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else:
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prev["next"] = curr["next"]
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return head
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prev = curr
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curr = curr["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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records = []
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curr = head
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while curr is not None:
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records.append((curr["name"], curr["phone"]))
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curr = curr["next"]
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records.sort(key=lambda x: x[0])
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return records
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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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idx = abs(hash(name)) % len(buckets)
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buckets[idx] = ll_insert(buckets[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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idx = abs(hash(name)) % len(buckets)
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return ll_find(buckets[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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idx = abs(hash(name)) % len(buckets)
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buckets[idx] = ll_delete(buckets[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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records = []
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for head in buckets:
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curr = head
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while curr is not None:
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records.append((curr["name"], curr["phone"]))
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curr = curr["next"]
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records.sort(key=lambda x: x[0])
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return records
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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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min_node = root["right"]
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while min_node["left"] is not None:
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min_node = min_node["left"]
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root["name"] = min_node["name"]
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root["phone"] = min_node["phone"]
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root["right"] = bst_delete(root["right"], min_node["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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records = []
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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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records.append((node["name"], node["phone"]))
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_inorder(node["right"])
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_inorder(root)
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return records
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BIN
MylnikovAS/task_1/docs/data/performance.png
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BIN
MylnikovAS/task_1/docs/data/performance.png
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Binary file not shown.
109
MylnikovAS/task_1/docs/data/results.csv
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109
MylnikovAS/task_1/docs/data/results.csv
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@ -0,0 +1,109 @@
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Structure,Mode,Operation,Time (sec)
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LinkedList,random,insert (number 1),4.815837
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LinkedList,random,find (number 1),0.052892
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LinkedList,random,delete (number 1),0.027702
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LinkedList,random,insert (number 2),4.566321
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LinkedList,random,find (number 2),0.049406
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LinkedList,random,delete (number 2),0.024055
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LinkedList,random,insert (number 3),4.912175
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LinkedList,random,find (number 3),0.048987
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LinkedList,random,delete (number 3),0.025564
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LinkedList,random,insert (number 4),5.096061
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LinkedList,random,find (number 4),0.059990
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LinkedList,random,delete (number 4),0.026717
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LinkedList,random,insert (number 5),5.182869
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LinkedList,random,find (number 5),0.055768
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LinkedList,random,delete (number 5),0.027361
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LinkedList,random,Insert (average),4.914653
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LinkedList,random,Find (average),0.053409
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LinkedList,random,Delete (average),0.026280
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LinkedList,sorted,insert (number 1),4.635120
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LinkedList,sorted,find (number 1),0.057343
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LinkedList,sorted,delete (number 1),0.028141
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LinkedList,sorted,insert (number 2),4.673462
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LinkedList,sorted,find (number 2),0.058540
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LinkedList,sorted,delete (number 2),0.030570
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LinkedList,sorted,insert (number 3),4.720830
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LinkedList,sorted,find (number 3),0.050661
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LinkedList,sorted,delete (number 3),0.026368
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LinkedList,sorted,insert (number 4),4.413700
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LinkedList,sorted,find (number 4),0.061699
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LinkedList,sorted,delete (number 4),0.040006
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LinkedList,sorted,insert (number 5),4.487595
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LinkedList,sorted,find (number 5),0.054366
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LinkedList,sorted,delete (number 5),0.031918
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LinkedList,sorted,Insert (average),4.586142
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LinkedList,sorted,Find (average),0.056522
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LinkedList,sorted,Delete (average),0.031401
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HashTable,random,insert (number 1),0.013673
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HashTable,random,find (number 1),0.000142
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HashTable,random,delete (number 1),0.000081
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HashTable,random,insert (number 2),0.012924
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HashTable,random,find (number 2),0.000111
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HashTable,random,delete (number 2),0.000056
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HashTable,random,insert (number 3),0.013575
|
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HashTable,random,find (number 3),0.000178
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||||
HashTable,random,delete (number 3),0.000090
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||||
HashTable,random,insert (number 4),0.012327
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||||
HashTable,random,find (number 4),0.000112
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HashTable,random,delete (number 4),0.000058
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HashTable,random,insert (number 5),0.012698
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||||
HashTable,random,find (number 5),0.000151
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HashTable,random,delete (number 5),0.000055
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HashTable,random,Insert (average),0.013039
|
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HashTable,random,Find (average),0.000139
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HashTable,random,Delete (average),0.000068
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HashTable,sorted,insert (number 1),0.012770
|
||||
HashTable,sorted,find (number 1),0.000128
|
||||
HashTable,sorted,delete (number 1),0.000067
|
||||
HashTable,sorted,insert (number 2),0.030806
|
||||
HashTable,sorted,find (number 2),0.000143
|
||||
HashTable,sorted,delete (number 2),0.000074
|
||||
HashTable,sorted,insert (number 3),0.011925
|
||||
HashTable,sorted,find (number 3),0.000142
|
||||
HashTable,sorted,delete (number 3),0.000072
|
||||
HashTable,sorted,insert (number 4),0.012686
|
||||
HashTable,sorted,find (number 4),0.000263
|
||||
HashTable,sorted,delete (number 4),0.000114
|
||||
HashTable,sorted,insert (number 5),0.011504
|
||||
HashTable,sorted,find (number 5),0.000139
|
||||
HashTable,sorted,delete (number 5),0.000075
|
||||
HashTable,sorted,Insert (average),0.015938
|
||||
HashTable,sorted,Find (average),0.000163
|
||||
HashTable,sorted,Delete (average),0.000080
|
||||
BST,random,insert (number 1),0.042690
|
||||
BST,random,find (number 1),0.000424
|
||||
BST,random,delete (number 1),0.000232
|
||||
BST,random,insert (number 2),0.042969
|
||||
BST,random,find (number 2),0.000436
|
||||
BST,random,delete (number 2),0.000248
|
||||
BST,random,insert (number 3),0.041771
|
||||
BST,random,find (number 3),0.000462
|
||||
BST,random,delete (number 3),0.000280
|
||||
BST,random,insert (number 4),0.046081
|
||||
BST,random,find (number 4),0.000392
|
||||
BST,random,delete (number 4),0.000199
|
||||
BST,random,insert (number 5),0.042080
|
||||
BST,random,find (number 5),0.000404
|
||||
BST,random,delete (number 5),0.000213
|
||||
BST,random,Insert (average),0.043118
|
||||
BST,random,Find (average),0.000424
|
||||
BST,random,Delete (average),0.000234
|
||||
BST,sorted,insert (number 1),21.678231
|
||||
BST,sorted,find (number 1),0.198191
|
||||
BST,sorted,delete (number 1),0.080743
|
||||
BST,sorted,insert (number 2),25.945965
|
||||
BST,sorted,find (number 2),0.197616
|
||||
BST,sorted,delete (number 2),0.095071
|
||||
BST,sorted,insert (number 3),25.663677
|
||||
BST,sorted,find (number 3),0.194259
|
||||
BST,sorted,delete (number 3),0.081219
|
||||
BST,sorted,insert (number 4),22.098788
|
||||
BST,sorted,find (number 4),0.197365
|
||||
BST,sorted,delete (number 4),0.090777
|
||||
BST,sorted,insert (number 5),22.467530
|
||||
BST,sorted,find (number 5),0.168119
|
||||
BST,sorted,delete (number 5),0.071693
|
||||
BST,sorted,Insert (average),23.570838
|
||||
BST,sorted,Find (average),0.191110
|
||||
BST,sorted,Delete (average),0.083900
|
||||
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