328 lines
9.6 KiB
Python
328 lines
9.6 KiB
Python
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import time
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import random
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import csv
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import os
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import sys
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sys.setrecursionlimit(20000)
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BASE = os.path.dirname(os.path.abspath(__file__))
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DATA_PATH = BASE
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N = 10000
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REPEAT = 5
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def ll_insert(head, name, phone):
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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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curr = head
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while curr:
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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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if head is None:
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return None
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if head["name"] == name:
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return head["next"]
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curr = head
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while curr["next"]:
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if curr["next"]["name"] == name:
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curr["next"] = curr["next"]["next"]
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return head
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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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result = []
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curr = head
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while curr:
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result.append((curr["name"], curr["phone"]))
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curr = curr["next"]
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result.sort()
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return result
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BUCKET_SIZE = 1000
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def ht_insert(buckets, name, phone):
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idx = 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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idx = 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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idx = 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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result = []
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for bucket in buckets:
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curr = bucket
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while curr:
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result.append((curr["name"], curr["phone"]))
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curr = curr["next"]
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result.sort()
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return result
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def bst_insert(root, name, phone):
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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["left"] = bst_insert(root["left"], name, phone)
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elif name > root["name"]:
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root["right"] = bst_insert(root["right"], name, phone)
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else:
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root["phone"] = phone
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return root
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def bst_find(root, name):
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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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if name < root["name"]:
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return bst_find(root["left"], name)
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return bst_find(root["right"], name)
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def bst_delete(root, name):
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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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temp = root["right"]
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while temp["left"]:
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temp = temp["left"]
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root["name"] = temp["name"]
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root["phone"] = temp["phone"]
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root["right"] = bst_delete(root["right"], temp["name"])
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return root
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def bst_list_all(root):
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result = []
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def walk(node):
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if node is None:
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return
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walk(node["left"])
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result.append((node["name"], node["phone"]))
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walk(node["right"])
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walk(root)
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return result
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def make_records(n):
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records = []
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for i in range(n):
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records.append((f"User_{i:05d}", f"8-900-{i % 10000:04d}"))
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return records
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records_all = make_records(N)
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records_shuffled = records_all[:]
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random.shuffle(records_shuffled)
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records_sorted = sorted(records_all)
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all_names = [name for name, phone in records_all]
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find_existing = random.sample(all_names, 100)
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find_missing = [f"None_{i}" for i in range(10)]
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find_names = find_existing + find_missing
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random.shuffle(find_names)
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delete_names = random.sample(all_names, 50)
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all_results = []
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summary = []
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def build_structure(struct_type, records):
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if struct_type == "LinkedList":
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head = None
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for name, phone in records:
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head = ll_insert(head, name, phone)
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return head
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if struct_type == "HashTable":
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buckets = [None] * BUCKET_SIZE
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for name, phone in records:
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ht_insert(buckets, name, phone)
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return buckets
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root = None
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for name, phone in records:
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root = bst_insert(root, name, phone)
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return root
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def do_find(struct_type, container, names):
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for name in names:
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if struct_type == "LinkedList":
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ll_find(container, name)
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elif struct_type == "HashTable":
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ht_find(container, name)
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else:
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bst_find(container, name)
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def do_delete(struct_type, container, names):
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if struct_type == "LinkedList":
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for name in names:
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container = ll_delete(container, name)
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return container
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if struct_type == "HashTable":
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for name in names:
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ht_delete(container, name)
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return container
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for name in names:
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container = bst_delete(container, name)
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return container
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def run_one_test(struct_type, mode_name, records):
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ins_times = []
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find_times = []
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del_times = []
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for run in range(REPEAT):
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start = time.perf_counter()
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container = build_structure(struct_type, records)
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ins_times.append(time.perf_counter() - start)
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start = time.perf_counter()
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do_find(struct_type, container, find_names)
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find_times.append(time.perf_counter() - start)
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start = time.perf_counter()
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do_delete(struct_type, container, delete_names)
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del_times.append(time.perf_counter() - start)
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all_results.append([
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struct_type, mode_name, f"Run {run + 1}",
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ins_times[-1], find_times[-1], del_times[-1],
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])
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avg_ins = sum(ins_times) / REPEAT
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avg_find = sum(find_times) / REPEAT
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avg_del = sum(del_times) / REPEAT
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all_results.append([
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struct_type, mode_name, "AVERAGE", avg_ins, avg_find, avg_del,
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])
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summary.append({
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"name": struct_type,
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"mode": mode_name,
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"ins": avg_ins,
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"find": avg_find,
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"del": avg_del,
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})
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print("Запуск экспериментов...")
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for mode_name, data in [("случайный", records_shuffled), ("сортированный", records_sorted)]:
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for struct_type in ["LinkedList", "HashTable", "BST"]:
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print(f" {struct_type} ({mode_name})")
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run_one_test(struct_type, mode_name, data)
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csv_path = os.path.join(DATA_PATH, "results.csv")
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with open(csv_path, "w", newline="", encoding="utf-8-sig") as f:
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writer = csv.writer(f, delimiter=";")
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writer.writerow(["Структура", "Режим", "Итерация", "Вставка", "Поиск", "Удаление"])
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writer.writerows(all_results)
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print("CSV сохранён:", csv_path)
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try:
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import matplotlib.pyplot as plt
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plt.rcParams["font.sans-serif"] = ["Segoe UI", "Arial", "Tahoma", "DejaVu Sans"]
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plt.rcParams["axes.unicode_minus"] = False
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labels = ["insert", "find", "delete"]
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structs = ["LinkedList", "HashTable", "BST"]
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colors = ["#5dade2", "#e67e22", "#58d68d"]
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fig1, axs = plt.subplots(1, 3, figsize=(15, 5))
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fig1.suptitle("Влияние порядка данных")
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for i, s_name in enumerate(structs):
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rand_d = next(r for r in summary if r["name"] == s_name and r["mode"] == "случайный")
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sort_d = next(r for r in summary if r["name"] == s_name and r["mode"] == "сортированный")
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x = [0, 1, 2]
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w = 0.35
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axs[i].bar([p - w / 2 for p in x], [rand_d["ins"], rand_d["find"], rand_d["del"]], w, label="случайный")
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axs[i].bar([p + w / 2 for p in x], [sort_d["ins"], sort_d["find"], sort_d["del"]], w, label="сортированный")
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axs[i].set_title(s_name)
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axs[i].set_xticks(x)
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axs[i].set_xticklabels(labels)
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axs[i].legend()
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axs[i].grid(axis="y", alpha=0.3)
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plt.tight_layout()
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plt.savefig(os.path.join(DATA_PATH, "order_impact.png"))
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plt.close()
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fig2, axs2 = plt.subplots(1, 3, figsize=(15, 5))
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fig2.suptitle(f"Сравнение структур (N={N})")
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for i, key in enumerate(["ins", "find", "del"]):
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vals = []
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names = []
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for r in summary:
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names.append(f"{r['name']}\n({r['mode'][:4]})")
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vals.append(r[key])
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axs2[i].bar(names, vals, color=colors * 2)
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axs2[i].set_title(labels[i])
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axs2[i].tick_params(axis="x", rotation=20)
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plt.tight_layout()
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plt.savefig(os.path.join(DATA_PATH, "struct_comparison.png"))
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plt.close()
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print("Графики сохранены")
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except ImportError:
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print("matplotlib не установлен")
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report_path = os.path.join(os.path.dirname(BASE), "report.md")
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with open(report_path, "w", encoding="utf-8-sig") as f:
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f.write("# Отчёт: сравнение структур данных\n\n")
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f.write(f"N = {N}, повторов = {REPEAT}\n\n")
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f.write("| Структура | Режим | Вставка (с) | Поиск (с) | Удаление (с) |\n")
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f.write("| --- | --- | --- | --- | --- |\n")
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for r in summary:
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f.write(
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f"| {r['name']} | {r['mode']} | {r['ins']:.6f} | {r['find']:.6f} | {r['del']:.6f} |\n"
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)
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f.write("\n## Графики\n\n")
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f.write("\n\n")
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f.write("\n\n")
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f.write("## Выводы\n\n")
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f.write("- BST на отсортированных данных сильно тормозит (вырождение дерева).\n")
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f.write("- Хеш-таблица быстра на поиске и слабо зависит от порядка вставки.\n")
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f.write("- Связный список медленный при поиске.\n")
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f.write("- Для частого поиска предпочтительна хеш-таблица.\n")
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print("Отчёт:", report_path)
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print("Готово.")
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