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8 Commits
tsareveo-p
...
develop
| Author | SHA1 | Date | |
|---|---|---|---|
| 7465167739 | |||
| 657f864ed6 | |||
| faf54114a0 | |||
| f1d9a64911 | |||
| c12f9ef1bf | |||
| 972243d118 | |||
| 58d0447aae | |||
| 52ab70ee71 |
0
PaulVA/429
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BIN
PaulVA/lab1/docs/data/graph_delete.png
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After Width: | Height: | Size: 13 KiB |
BIN
PaulVA/lab1/docs/data/graph_find.png
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After Width: | Height: | Size: 13 KiB |
BIN
PaulVA/lab1/docs/data/graph_insert.png
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After Width: | Height: | Size: 13 KiB |
19
PaulVA/lab1/docs/data/results.csv
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@ -0,0 +1,19 @@
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structure,order,operation,run1,run2,run3,run4,run5,average
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LinkedList,random,insert,3.000600399999712,3.022712899999533,2.9421689999999217,2.9075659000000087,3.0319512999994913,2.980999899999733
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LinkedList,random,find,0.031094500000108383,0.02800200000001496,0.034349299999121286,0.029372199999670556,0.03242119999958959,0.031047839999700955
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LinkedList,random,delete,0.017322699999567703,0.0368361000000732,0.04029200000059063,0.03775789999963308,0.03554420000000391,0.033550579999973705
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HashTable,random,insert,0.011551699999472476,0.012756400000398571,0.011765299999751733,0.011679000000185624,0.011983400000644906,0.011947160000090662
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HashTable,random,find,0.00012409999999363208,0.00011009999980160501,0.0001415999995515449,0.00010400000064691994,0.00010089999977935804,0.000116139999954612
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HashTable,random,delete,6.38999999864609e-05,6.779999966965988e-05,6.0600000324484427e-05,6.070000017643906e-05,6.0600000324484427e-05,6.272000009630574e-05
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BST,random,insert,0.014788199999202334,0.014159299999846553,0.013975800000480376,0.014118900000539725,0.013331299999663315,0.01407469999994646
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BST,random,find,0.00013829999988956843,0.00011389999963284936,0.00011369999992894009,0.00011379999978089472,0.00011439999980211724,0.00011881999980687397
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BST,random,delete,8.690000049682567e-05,6.450000000768341e-05,6.2199999774748e-05,6.209999992279336e-05,6.229999962670263e-05,6.759999996575061e-05
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LinkedList,sorted,insert,2.4411346000006233,2.36463619999995,2.2797248999995645,2.2860746000005747,2.2526011999998445,2.3248343000001115
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LinkedList,sorted,find,0.024703000000044995,0.02455259999987902,0.02468479999970441,0.02444869999999355,0.02606350000041857,0.02489052000000811
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|
LinkedList,sorted,delete,0.012835599999561964,0.027673999999933585,0.027570299999752024,0.02708100000018021,0.02999909999925876,0.02503199999973731
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|
HashTable,sorted,insert,0.011780100000578386,0.010850699999537028,0.010314100000869075,0.010621500000524975,0.011015500000212342,0.010916380000344362
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HashTable,sorted,find,0.0001464000006308197,0.00017980000029638177,0.00016909999976633117,0.00012620000052265823,0.00023630000032426324,0.0001715600003080908
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HashTable,sorted,delete,0.00016370000048482325,0.00018089999957737746,0.0001443999999537482,7.579999964946182e-05,6.469999971159268e-05,0.0001258999998754007
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BST,sorted,insert,3.5400651999998445,3.5145174999997835,3.5583661999999094,3.5149656000003233,3.481246600000304,3.521832220000033
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BST,sorted,find,0.03275260000009439,0.030442500000390282,0.02994349999971746,0.030269500000031258,0.030329999999594293,0.030747619999965538
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BST,sorted,delete,0.012705400000413647,0.01333390000036161,0.013192000000344706,0.013699000000087835,0.013079800000014075,0.013202020000244374
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34
PaulVA/lab1/docs/report.md
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@ -0,0 +1,34 @@
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Лабораторная работа 1
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Цель работы
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Нужно было сделать три структуры данных и проверить как они работают на телефонном справочнике.
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Ход работы
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Сделал связный список хеш таблицу и двоичное дерево поиска. Для всех структур сделал добавление поиск удаление и вывод записей. Для проверки создал 10000 записей с именами User\_00000 и т.д. Потом проверил работу со случайным порядком и с отсортированным порядком. Каждый эксперимент повторял 5 раз.
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Результаты
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Результаты сохранились в results.csv. Также сделал графики для добавления поиска и удаления. По результатам видно что связный список медленно ищет записи потому что нужно идти по элементам. Хеш таблица работает примерно одинаково при разном порядке записей. У двоичного дерева порядок записей влияет намного сильнее. Если добавлять записи по порядку дерево становится похожим на обычный список и работает медленнее.
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Вывод
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В работе я сделал три структуры данных и проверил их работу. Самой удобной для телефонного справочника получилась хеш таблица. Связный список проще но поиск медленный. Двоичное дерево может работать быстро но сильно зависит от порядка добавления данных.
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185
PaulVA/lab1/experiments.py
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@ -0,0 +1,185 @@
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import random
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import time
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import csv
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import os
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from phonebook import *
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N = 10000
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REPEATS = 5
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def generate_test_data():
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records = [
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(f"User_{i:05d}", f"+7900000{i:04d}")
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for i in range(N)
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]
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records_shuffled = records.copy()
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random.shuffle(records_shuffled)
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records_sorted = records.copy()
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return records_shuffled, records_sorted
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def measure_experiment(insert_function, find_function, delete_function, records):
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insert_times = []
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find_times = []
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delete_times = []
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for _ in range(REPEATS):
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structure = None
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start = time.perf_counter()
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for name, phone in records:
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structure = insert_function(structure, name, phone)
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insert_times.append(time.perf_counter() - start)
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structure_for_find = structure
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names = [name for name, phone in records]
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search_names = random.sample(names, 100) + [
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"NotFound_001",
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"NotFound_002",
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"NotFound_003",
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"NotFound_004",
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"NotFound_005",
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"NotFound_006",
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"NotFound_007",
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"NotFound_008",
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"NotFound_009",
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"NotFound_010"
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]
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for _ in range(REPEATS):
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start = time.perf_counter()
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for name in search_names:
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find_function(structure_for_find, name)
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find_times.append(time.perf_counter() - start)
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delete_names = random.sample(names, 50)
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for _ in range(REPEATS):
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structure = structure_for_find
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start = time.perf_counter()
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for name in delete_names:
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structure = delete_function(structure, name)
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delete_times.append(time.perf_counter() - start)
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return insert_times, find_times, delete_times
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def measure_hash(records):
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insert_times = []
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find_times = []
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delete_times = []
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names = [name for name, phone in records]
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search_names = random.sample(names, 100) + [
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f"NotFound_{i:03d}" for i in range(10)
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]
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delete_names = random.sample(names, 50)
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for _ in range(REPEATS):
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buckets = ht_create()
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start = time.perf_counter()
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for name, phone in records:
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ht_insert(buckets, name, phone)
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insert_times.append(time.perf_counter() - start)
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structure_for_find = buckets
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for _ in range(REPEATS):
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start = time.perf_counter()
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for name in search_names:
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ht_find(structure_for_find, name)
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find_times.append(time.perf_counter() - start)
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for _ in range(REPEATS):
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buckets = structure_for_find.copy()
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start = time.perf_counter()
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for name in delete_names:
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ht_delete(buckets, name)
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delete_times.append(time.perf_counter() - start)
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return insert_times, find_times, delete_times
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def average(values):
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return sum(values) / len(values)
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def run():
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records_shuffled, records_sorted = generate_test_data()
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results = []
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for order_name, records in [
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("random", records_shuffled),
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("sorted", records_sorted)
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]:
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print("Order:", order_name)
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ll = measure_experiment(
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ll_insert,
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ll_find,
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ll_delete,
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records
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)
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results.append(["LinkedList", order_name, "insert", *ll[0]])
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results.append(["LinkedList", order_name, "find", *ll[1]])
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results.append(["LinkedList", order_name, "delete", *ll[2]])
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ht = measure_hash(records)
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results.append(["HashTable", order_name, "insert", *ht[0]])
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results.append(["HashTable", order_name, "find", *ht[1]])
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results.append(["HashTable", order_name, "delete", *ht[2]])
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bst = measure_experiment(
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bst_insert,
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bst_find,
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bst_delete,
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records
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)
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results.append(["BST", order_name, "insert", *bst[0]])
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results.append(["BST", order_name, "find", *bst[1]])
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results.append(["BST", order_name, "delete", *bst[2]])
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os.makedirs("docs/data", exist_ok=True)
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with open("docs/data/results.csv", "w", newline="", encoding="utf-8") as file:
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writer = csv.writer(file)
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writer.writerow([
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"structure",
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"order",
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"operation",
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"run1",
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"run2",
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"run3",
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"run4",
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"run5",
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"average"
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|
])
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for row in results:
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writer.writerow(row + [average(row[3:])])
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|
print("Results saved to docs/data/results.csv")
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|
if __name__ == "__main__":
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|
run()
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56
PaulVA/lab1/graphs.py
Normal file
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@ -0,0 +1,56 @@
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|
import csv
|
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|
import os
|
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|
import matplotlib.pyplot as plt
|
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|
|
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|
data = []
|
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|
|
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|
with open("docs/data/results.csv", "r", encoding="utf-8") as file:
|
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|
reader = csv.DictReader(file)
|
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|
|
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|
for row in reader:
|
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|
data.append(row)
|
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|
|
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|
def get_average(structure, order, operation):
|
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|
for row in data:
|
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|
if (
|
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|
row["structure"] == structure
|
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|
and row["order"] == order
|
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|
and row["operation"] == operation
|
||||||
|
):
|
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|
return float(row["average"])
|
||||||
|
|
||||||
|
return 0
|
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|
|
||||||
|
structures = ["LinkedList", "HashTable", "BST"]
|
||||||
|
orders = ["random", "sorted"]
|
||||||
|
|
||||||
|
os.makedirs("docs/data", exist_ok=True)
|
||||||
|
|
||||||
|
for operation in ["insert", "find", "delete"]:
|
||||||
|
random_values = [
|
||||||
|
get_average(s, "random", operation)
|
||||||
|
for s in structures
|
||||||
|
]
|
||||||
|
|
||||||
|
sorted_values = [
|
||||||
|
get_average(s, "sorted", operation)
|
||||||
|
for s in structures
|
||||||
|
]
|
||||||
|
|
||||||
|
x = range(len(structures))
|
||||||
|
|
||||||
|
plt.figure()
|
||||||
|
plt.bar([i - 0.2 for i in x], random_values, width=0.4, label="random")
|
||||||
|
plt.bar([i + 0.2 for i in x], sorted_values, width=0.4, label="sorted")
|
||||||
|
|
||||||
|
plt.xticks(list(x), structures)
|
||||||
|
plt.ylabel("Time, seconds")
|
||||||
|
plt.title(operation.capitalize() + " time")
|
||||||
|
plt.yscale("log")
|
||||||
|
plt.legend()
|
||||||
|
plt.tight_layout()
|
||||||
|
|
||||||
|
plt.savefig("docs/data/graph_" + operation + ".png")
|
||||||
|
plt.close()
|
||||||
|
|
||||||
|
print("Graphs saved to docs/data/")
|
||||||
211
PaulVA/lab1/phonebook.py
Normal file
|
|
@ -0,0 +1,211 @@
|
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|
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['next'] is not None:
|
||||||
|
if current['name'] == name:
|
||||||
|
current['phone'] = phone
|
||||||
|
return head
|
||||||
|
current = current['next']
|
||||||
|
|
||||||
|
if current['name'] == name:
|
||||||
|
current['phone'] = phone
|
||||||
|
else:
|
||||||
|
current['next'] = new_node
|
||||||
|
|
||||||
|
return head
|
||||||
|
|
||||||
|
def ll_find(head, name):
|
||||||
|
current = head
|
||||||
|
|
||||||
|
while current is not None:
|
||||||
|
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'] is not None:
|
||||||
|
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 is not None:
|
||||||
|
records.append((current['name'], current['phone']))
|
||||||
|
current = current['next']
|
||||||
|
|
||||||
|
records.sort(key=lambda x: x[0])
|
||||||
|
return records
|
||||||
|
|
||||||
|
def hash_function(name, table_size):
|
||||||
|
total = 0
|
||||||
|
|
||||||
|
for ch in name:
|
||||||
|
total = (total * 31 + ord(ch)) % table_size
|
||||||
|
|
||||||
|
return total
|
||||||
|
|
||||||
|
def ht_create(size=1000):
|
||||||
|
return [None] * size
|
||||||
|
|
||||||
|
def ht_insert(buckets, name, phone):
|
||||||
|
index = hash_function(name, len(buckets))
|
||||||
|
buckets[index] = ll_insert(buckets[index], name, phone)
|
||||||
|
return buckets
|
||||||
|
|
||||||
|
def ht_find(buckets, name):
|
||||||
|
index = hash_function(name, len(buckets))
|
||||||
|
return ll_find(buckets[index], name)
|
||||||
|
|
||||||
|
def ht_delete(buckets, name):
|
||||||
|
index = hash_function(name, len(buckets))
|
||||||
|
buckets[index] = ll_delete(buckets[index], name)
|
||||||
|
return buckets
|
||||||
|
|
||||||
|
def ht_list_all(buckets):
|
||||||
|
records = []
|
||||||
|
|
||||||
|
for bucket in buckets:
|
||||||
|
current = bucket
|
||||||
|
|
||||||
|
while current is not None:
|
||||||
|
records.append((current['name'], current['phone']))
|
||||||
|
current = current['next']
|
||||||
|
|
||||||
|
records.sort(key=lambda x: x[0])
|
||||||
|
return records
|
||||||
|
|
||||||
|
def bst_insert(root, name, phone):
|
||||||
|
new_node = {
|
||||||
|
'name': name,
|
||||||
|
'phone': phone,
|
||||||
|
'left': None,
|
||||||
|
'right': None
|
||||||
|
}
|
||||||
|
|
||||||
|
if root is None:
|
||||||
|
return new_node
|
||||||
|
|
||||||
|
current = root
|
||||||
|
|
||||||
|
while True:
|
||||||
|
if name < current['name']:
|
||||||
|
if current['left'] is None:
|
||||||
|
current['left'] = new_node
|
||||||
|
break
|
||||||
|
current = current['left']
|
||||||
|
|
||||||
|
elif name > current['name']:
|
||||||
|
if current['right'] is None:
|
||||||
|
current['right'] = new_node
|
||||||
|
break
|
||||||
|
current = current['right']
|
||||||
|
|
||||||
|
else:
|
||||||
|
current['phone'] = phone
|
||||||
|
break
|
||||||
|
|
||||||
|
return root
|
||||||
|
|
||||||
|
def bst_find(root, name):
|
||||||
|
current = root
|
||||||
|
|
||||||
|
while current is not None:
|
||||||
|
if name == current['name']:
|
||||||
|
return current['phone']
|
||||||
|
|
||||||
|
if name < current['name']:
|
||||||
|
current = current['left']
|
||||||
|
else:
|
||||||
|
current = current['right']
|
||||||
|
|
||||||
|
return None
|
||||||
|
|
||||||
|
def bst_delete(root, name):
|
||||||
|
parent = None
|
||||||
|
current = root
|
||||||
|
|
||||||
|
while current is not None and current['name'] != name:
|
||||||
|
parent = current
|
||||||
|
|
||||||
|
if name < current['name']:
|
||||||
|
current = current['left']
|
||||||
|
else:
|
||||||
|
current = current['right']
|
||||||
|
|
||||||
|
if current is None:
|
||||||
|
return root
|
||||||
|
|
||||||
|
if current['left'] is None:
|
||||||
|
child = current['right']
|
||||||
|
|
||||||
|
elif current['right'] is None:
|
||||||
|
child = current['left']
|
||||||
|
|
||||||
|
else:
|
||||||
|
successor_parent = current
|
||||||
|
successor = current['right']
|
||||||
|
|
||||||
|
while successor['left'] is not None:
|
||||||
|
successor_parent = successor
|
||||||
|
successor = successor['left']
|
||||||
|
|
||||||
|
current['name'] = successor['name']
|
||||||
|
current['phone'] = successor['phone']
|
||||||
|
|
||||||
|
if successor_parent['left'] == successor:
|
||||||
|
successor_parent['left'] = successor['right']
|
||||||
|
else:
|
||||||
|
successor_parent['right'] = successor['right']
|
||||||
|
|
||||||
|
return root
|
||||||
|
|
||||||
|
if parent is None:
|
||||||
|
return child
|
||||||
|
|
||||||
|
if parent['left'] == current:
|
||||||
|
parent['left'] = child
|
||||||
|
else:
|
||||||
|
parent['right'] = child
|
||||||
|
|
||||||
|
return root
|
||||||
|
|
||||||
|
def bst_list_all(root):
|
||||||
|
records = []
|
||||||
|
|
||||||
|
def inorder(node):
|
||||||
|
if node is None:
|
||||||
|
return
|
||||||
|
|
||||||
|
inorder(node['left'])
|
||||||
|
records.append((node['name'], node['phone']))
|
||||||
|
inorder(node['right'])
|
||||||
|
|
||||||
|
inorder(root)
|
||||||
|
|
||||||
|
return records
|
||||||
BIN
PaulVA/lab2/docs/data/dead_time.png
Normal file
|
After Width: | Height: | Size: 15 KiB |
BIN
PaulVA/lab2/docs/data/empty_time.png
Normal file
|
After Width: | Height: | Size: 12 KiB |
BIN
PaulVA/lab2/docs/data/large_time.png
Normal file
|
After Width: | Height: | Size: 15 KiB |
BIN
PaulVA/lab2/docs/data/noexit_time.png
Normal file
|
After Width: | Height: | Size: 16 KiB |
16
PaulVA/lab2/docs/data/results.csv
Normal file
|
|
@ -0,0 +1,16 @@
|
||||||
|
maze,strategy,time_ms,visited_cells,path_length
|
||||||
|
simple.txt,BFS,0.01464000015403144,11.0,6.0
|
||||||
|
simple.txt,DFS,0.010180000390391797,9.0,8.0
|
||||||
|
simple.txt,A*,0.017740000475896522,9.0,6.0
|
||||||
|
dead.txt,BFS,0.3642999996372964,307.0,35.0
|
||||||
|
dead.txt,DFS,0.23493999906349927,279.0,151.0
|
||||||
|
dead.txt,A*,0.38374000068870373,235.0,35.0
|
||||||
|
large.txt,BFS,23.894459999428364,6812.0,2329.0
|
||||||
|
large.txt,DFS,84.77875999960816,6796.0,4537.0
|
||||||
|
large.txt,A*,28.69542000044021,6791.0,2329.0
|
||||||
|
empty.txt,BFS,1.2770400004228577,1176.0,48.0
|
||||||
|
empty.txt,DFS,7.602279999264283,2304.0,1176.0
|
||||||
|
empty.txt,A*,0.10093999881064519,48.0,48.0
|
||||||
|
noexit.txt,BFS,0.003699999797390774,1.0,0.0
|
||||||
|
noexit.txt,DFS,0.0032000003557186574,1.0,0.0
|
||||||
|
noexit.txt,A*,0.004120000085094944,1.0,0.0
|
||||||
|
BIN
PaulVA/lab2/docs/data/simple_time.png
Normal file
|
After Width: | Height: | Size: 16 KiB |
212
PaulVA/lab2/docs/report.md
Normal file
|
|
@ -0,0 +1,212 @@
|
||||||
|
Лабораторная работа 2
|
||||||
|
|
||||||
|
Поиск выхода из лабиринта
|
||||||
|
|
||||||
|
Цель работы
|
||||||
|
-----------
|
||||||
|
Цель работы состоит в реализации программы для поиска выхода из лабиринта с использованием объектно ориентированного подхода и паттернов проектирования
|
||||||
|
|
||||||
|
В программе реализована загрузка лабиринта из файла несколько алгоритмов поиска и сравнение их работы
|
||||||
|
|
||||||
|
Структура программы
|
||||||
|
-------------------
|
||||||
|
В программе используются классы Cell для отдельной клетки лабиринта и Maze для самого лабиринта
|
||||||
|
|
||||||
|
Для загрузки используется MazeBuilder и его реализация TextFileMazeBuilder
|
||||||
|
|
||||||
|
Для поиска пути используется общий класс PathFindingStrategy и три алгоритма BFSStrategy DFSStrategy и AStarStrategy
|
||||||
|
|
||||||
|
За хранение результатов отвечает SearchStats а запуск поиска выполняет MazeSolver
|
||||||
|
|
||||||
|
Для вывода информации используются Observer и ConsoleView
|
||||||
|
|
||||||
|
Использованные паттерны
|
||||||
|
-----------------------
|
||||||
|
В работе использованы три паттерна Builder Strategy и Observer
|
||||||
|
|
||||||
|
Builder используется для загрузки лабиринта из текстового файла
|
||||||
|
|
||||||
|
TextFileMazeBuilder читает файл и создаёт объект Maze
|
||||||
|
|
||||||
|
В файле символ # обозначает стену пробел обозначает свободную клетку S является началом а E выходом
|
||||||
|
|
||||||
|
Использование Builder позволяет отдельно реализовать загрузку лабиринта и сам класс лабиринта
|
||||||
|
|
||||||
|
Strategy используется для выбора алгоритма поиска
|
||||||
|
|
||||||
|
В программе реализованы BFS DFS и A*
|
||||||
|
|
||||||
|
Все алгоритмы имеют общий интерфейс PathFindingStrategy поэтому в MazeSolver можно менять алгоритм без изменения самого решателя
|
||||||
|
|
||||||
|
Observer используется для вывода информации о поиске
|
||||||
|
|
||||||
|
MazeSolver отправляет события а ConsoleView получает их и выводит информацию в консоль
|
||||||
|
|
||||||
|
Таким образом вывод отделён от основной логики поиска
|
||||||
|
|
||||||
|
Алгоритмы поиска
|
||||||
|
----------------
|
||||||
|
BFS использует очередь и при обычных условиях находит кратчайший путь в лабиринте без весов
|
||||||
|
|
||||||
|
DFS использует стек и может найти путь быстрее но найденный путь не обязательно будет кратчайшим
|
||||||
|
|
||||||
|
A* использует очередь с приоритетом и манхэттенскую эвристику поэтому старается в первую очередь проверять клетки которые находятся ближе к выходу
|
||||||
|
|
||||||
|
Схема классов
|
||||||
|
-------------
|
||||||
|
classDiagram
|
||||||
|
|
||||||
|
class Cell {
|
||||||
|
x
|
||||||
|
y
|
||||||
|
is_wall
|
||||||
|
is_start
|
||||||
|
is_exit
|
||||||
|
is_passable()
|
||||||
|
}
|
||||||
|
|
||||||
|
class Maze {
|
||||||
|
width
|
||||||
|
height
|
||||||
|
cells
|
||||||
|
start
|
||||||
|
exit
|
||||||
|
get_cell()
|
||||||
|
get_neighbors()
|
||||||
|
}
|
||||||
|
|
||||||
|
class MazeBuilder {
|
||||||
|
build_from_file()
|
||||||
|
}
|
||||||
|
|
||||||
|
class TextFileMazeBuilder {
|
||||||
|
build_from_file()
|
||||||
|
}
|
||||||
|
|
||||||
|
class PathFindingStrategy {
|
||||||
|
find_path()
|
||||||
|
}
|
||||||
|
|
||||||
|
class BFSStrategy {
|
||||||
|
find_path()
|
||||||
|
}
|
||||||
|
|
||||||
|
class DFSStrategy {
|
||||||
|
find_path()
|
||||||
|
}
|
||||||
|
|
||||||
|
class AStarStrategy {
|
||||||
|
find_path()
|
||||||
|
}
|
||||||
|
|
||||||
|
class SearchStats {
|
||||||
|
path
|
||||||
|
time_ms
|
||||||
|
visited_count
|
||||||
|
path_length
|
||||||
|
}
|
||||||
|
|
||||||
|
class MazeSolver {
|
||||||
|
maze
|
||||||
|
strategy
|
||||||
|
set_strategy()
|
||||||
|
solve()
|
||||||
|
}
|
||||||
|
|
||||||
|
class Observer {
|
||||||
|
update()
|
||||||
|
}
|
||||||
|
|
||||||
|
class ConsoleView {
|
||||||
|
update()
|
||||||
|
}
|
||||||
|
|
||||||
|
MazeBuilder <|-- TextFileMazeBuilder
|
||||||
|
PathFindingStrategy <|-- BFSStrategy
|
||||||
|
PathFindingStrategy <|-- DFSStrategy
|
||||||
|
PathFindingStrategy <|-- AStarStrategy
|
||||||
|
Observer <|-- ConsoleView
|
||||||
|
MazeSolver --> Maze
|
||||||
|
MazeSolver --> PathFindingStrategy
|
||||||
|
MazeSolver --> Observer
|
||||||
|
Maze --> Cell
|
||||||
|
Тестирование
|
||||||
|
------------
|
||||||
|
Для проверки использовалось пять разных лабиринтов
|
||||||
|
|
||||||
|
simple.txt представляет простой лабиринт dead.txt содержит тупики large.txt является большим запутанным лабиринтом empty.txt не содержит стен а в noexit.txt выход недостижим
|
||||||
|
|
||||||
|
Каждый алгоритм запускался пять раз
|
||||||
|
|
||||||
|
Во время эксперимента измерялось время поиска количество посещённых клеток и длина найденного пути
|
||||||
|
|
||||||
|
Результаты сохранялись в файл results.csv
|
||||||
|
|
||||||
|
Результаты
|
||||||
|
----------
|
||||||
|
simple.txt
|
||||||
|
Алгоритм Время мс Посещено Путь
|
||||||
|
BFS 0.01464 11 6
|
||||||
|
DFS 0.01018 9 8
|
||||||
|
A* 0.01774 9 6
|
||||||
|
|
||||||
|
Все алгоритмы работают быстро
|
||||||
|
|
||||||
|
BFS и A* нашли более короткий путь чем DFS
|
||||||
|
|
||||||
|
dead.txt
|
||||||
|
Алгоритм Время мс Посещено Путь
|
||||||
|
BFS 0.36430 307 35
|
||||||
|
DFS 0.23494 279 151
|
||||||
|
A* 0.38374 235 35
|
||||||
|
|
||||||
|
DFS работал немного быстрее но нашёл более длинный путь
|
||||||
|
|
||||||
|
BFS и A* нашли короткий путь
|
||||||
|
|
||||||
|
large.txt
|
||||||
|
Алгоритм Время мс Посещено Путь
|
||||||
|
BFS 23.89446 6812 2329
|
||||||
|
DFS 84.77876 6796 4537
|
||||||
|
A* 28.69542 6791 2329
|
||||||
|
|
||||||
|
На большом лабиринте DFS показал худшее время и самый длинный путь
|
||||||
|
|
||||||
|
BFS и A* нашли одинаковый путь
|
||||||
|
|
||||||
|
empty.txt
|
||||||
|
Алгоритм Время мс Посещено Путь
|
||||||
|
BFS 1.277
|
||||||
|
|
||||||
|
|
||||||
|
04 1176 48
|
||||||
|
DFS 7.60228 2304 1176
|
||||||
|
A* 0.10094 48 48
|
||||||
|
|
||||||
|
В лабиринте без стен лучше всего показал себя A*
|
||||||
|
|
||||||
|
Он посетил меньше всего клеток и работал быстрее
|
||||||
|
|
||||||
|
noexit.txt
|
||||||
|
Алгоритм Время мс Посещено Путь
|
||||||
|
BFS 0.00370 1 0
|
||||||
|
DFS 0.00320 1 0
|
||||||
|
A* 0.00412 1 0
|
||||||
|
|
||||||
|
В этом лабиринте выход недостижим поэтому все алгоритмы быстро закончили поиск
|
||||||
|
|
||||||
|
Графики
|
||||||
|
-------
|
||||||
|
Для сравнения времени работы были построены графики для каждого лабиринта
|
||||||
|
|
||||||
|
Графики находятся в папке docs/data
|
||||||
|
|
||||||
|
simple_time.png dead_time.png large_time.png empty_time.png и noexit_time.png
|
||||||
|
|
||||||
|
Вывод
|
||||||
|
-----
|
||||||
|
В работе была создана программа для поиска выхода из лабиринта
|
||||||
|
|
||||||
|
Были реализованы BFS DFS и A* а также использованы паттерны Builder Strategy и Observer
|
||||||
|
|
||||||
|
По результатам эксперимента BFS хорошо подходит для поиска кратчайшего пути DFS может найти путь быстрее но он не всегда получается коротким A* хорошо показывает себя на больших и открытых лабиринтах
|
||||||
93
PaulVA/lab2/experiments.py
Normal file
|
|
@ -0,0 +1,93 @@
|
||||||
|
import csv
|
||||||
|
import os
|
||||||
|
|
||||||
|
from maze_solver import (
|
||||||
|
TextFileMazeBuilder,
|
||||||
|
MazeSolver,
|
||||||
|
BFSStrategy,
|
||||||
|
DFSStrategy,
|
||||||
|
AStarStrategy
|
||||||
|
)
|
||||||
|
|
||||||
|
REPEATS = 5
|
||||||
|
|
||||||
|
MAZES = [
|
||||||
|
"simple.txt",
|
||||||
|
"dead.txt",
|
||||||
|
"large.txt",
|
||||||
|
"empty.txt",
|
||||||
|
"noexit.txt"
|
||||||
|
]
|
||||||
|
|
||||||
|
STRATEGIES = [
|
||||||
|
("BFS", BFSStrategy()),
|
||||||
|
("DFS", DFSStrategy()),
|
||||||
|
("A*", AStarStrategy())
|
||||||
|
]
|
||||||
|
|
||||||
|
def average(values):
|
||||||
|
return sum(values) / len(values)
|
||||||
|
|
||||||
|
def run():
|
||||||
|
builder = TextFileMazeBuilder()
|
||||||
|
results = []
|
||||||
|
|
||||||
|
for maze_name in MAZES:
|
||||||
|
filename = os.path.join("lab2", "mazes", maze_name)
|
||||||
|
|
||||||
|
print("Maze:", maze_name)
|
||||||
|
|
||||||
|
for strategy_name, strategy in STRATEGIES:
|
||||||
|
times = []
|
||||||
|
visited = []
|
||||||
|
path_lengths = []
|
||||||
|
|
||||||
|
for _ in range(REPEATS):
|
||||||
|
maze = builder.build_from_file(filename)
|
||||||
|
|
||||||
|
solver = MazeSolver(maze, strategy)
|
||||||
|
stats = solver.solve()
|
||||||
|
|
||||||
|
times.append(stats.time_ms)
|
||||||
|
visited.append(stats.visited_count)
|
||||||
|
path_lengths.append(stats.path_length)
|
||||||
|
|
||||||
|
results.append([
|
||||||
|
maze_name,
|
||||||
|
strategy_name,
|
||||||
|
average(times),
|
||||||
|
average(visited),
|
||||||
|
average(path_lengths)
|
||||||
|
])
|
||||||
|
|
||||||
|
print(
|
||||||
|
strategy_name,
|
||||||
|
"time =", average(times),
|
||||||
|
"visited =", average(visited),
|
||||||
|
"path =", average(path_lengths)
|
||||||
|
)
|
||||||
|
|
||||||
|
os.makedirs("lab2/docs/data", exist_ok=True)
|
||||||
|
|
||||||
|
with open(
|
||||||
|
"lab2/docs/data/results.csv",
|
||||||
|
"w",
|
||||||
|
newline="",
|
||||||
|
encoding="utf-8"
|
||||||
|
) as file:
|
||||||
|
writer = csv.writer(file)
|
||||||
|
|
||||||
|
writer.writerow([
|
||||||
|
"maze",
|
||||||
|
"strategy",
|
||||||
|
"time_ms",
|
||||||
|
"visited_cells",
|
||||||
|
"path_length"
|
||||||
|
])
|
||||||
|
|
||||||
|
writer.writerows(results)
|
||||||
|
|
||||||
|
print("Results saved to lab2/docs/data/results.csv")
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
run()
|
||||||
23
PaulVA/lab2/graphs.py
Normal file
|
|
@ -0,0 +1,23 @@
|
||||||
|
import csv
|
||||||
|
import matplotlib.pyplot as plt
|
||||||
|
|
||||||
|
with open("lab2/docs/data/results.csv", encoding="utf-8") as file:
|
||||||
|
rows = list(csv.DictReader(file))
|
||||||
|
|
||||||
|
mazes = ["simple.txt", "dead.txt", "large.txt", "empty.txt", "noexit.txt"]
|
||||||
|
strategies = ["BFS", "DFS", "A*"]
|
||||||
|
|
||||||
|
for maze in mazes:
|
||||||
|
values = []
|
||||||
|
|
||||||
|
for strategy in strategies:
|
||||||
|
for row in rows:
|
||||||
|
if row["maze"] == maze and row["strategy"] == strategy:
|
||||||
|
values.append(float(row["time_ms"]))
|
||||||
|
|
||||||
|
plt.bar(strategies, values)
|
||||||
|
plt.title("Время поиска: " + maze)
|
||||||
|
plt.xlabel("Стратегия")
|
||||||
|
plt.ylabel("Время, мс")
|
||||||
|
plt.savefig("lab2/docs/data/" + maze.replace(".txt", "_time.png"))
|
||||||
|
plt.close()
|
||||||
26
PaulVA/lab2/make_large.py
Normal file
|
|
@ -0,0 +1,26 @@
|
||||||
|
lines = []
|
||||||
|
|
||||||
|
for y in range(100):
|
||||||
|
row = [" "] * 100
|
||||||
|
|
||||||
|
if y == 0 or y == 99:
|
||||||
|
row = ["#"] * 100
|
||||||
|
else:
|
||||||
|
row[0] = "#"
|
||||||
|
row[99] = "#"
|
||||||
|
|
||||||
|
lines.append(row)
|
||||||
|
|
||||||
|
lines[1][1] = "S"
|
||||||
|
lines[98][98] = "E"
|
||||||
|
|
||||||
|
for x in range(4, 96, 4):
|
||||||
|
gap = 1 if (x // 4) % 2 == 0 else 98
|
||||||
|
|
||||||
|
for y in range(1, 99):
|
||||||
|
if y != gap:
|
||||||
|
lines[y][x] = "#"
|
||||||
|
|
||||||
|
with open("lab2/mazes/large.txt", "w", encoding="utf-8") as file:
|
||||||
|
for row in lines:
|
||||||
|
file.write("".join(row) + "\n")
|
||||||
284
PaulVA/lab2/maze_solver.py
Normal file
|
|
@ -0,0 +1,284 @@
|
||||||
|
from abc import ABC, abstractmethod
|
||||||
|
from collections import deque
|
||||||
|
import heapq
|
||||||
|
import time
|
||||||
|
|
||||||
|
class Cell:
|
||||||
|
def __init__(self, x, y):
|
||||||
|
self.x = x
|
||||||
|
self.y = y
|
||||||
|
self.is_wall = False
|
||||||
|
self.is_start = False
|
||||||
|
self.is_exit = False
|
||||||
|
|
||||||
|
def is_passable(self):
|
||||||
|
return not self.is_wall
|
||||||
|
|
||||||
|
class Maze:
|
||||||
|
def __init__(self, width, height):
|
||||||
|
self.width = width
|
||||||
|
self.height = height
|
||||||
|
self.cells = []
|
||||||
|
self.start = None
|
||||||
|
self.exit = None
|
||||||
|
|
||||||
|
for y in range(height):
|
||||||
|
row = []
|
||||||
|
|
||||||
|
for x in range(width):
|
||||||
|
row.append(Cell(x, y))
|
||||||
|
|
||||||
|
self.cells.append(row)
|
||||||
|
|
||||||
|
def get_cell(self, x, y):
|
||||||
|
if 0 <= x < self.width and 0 <= y < self.height:
|
||||||
|
return self.cells[y][x]
|
||||||
|
|
||||||
|
return None
|
||||||
|
|
||||||
|
def get_neighbors(self, cell):
|
||||||
|
neighbors = []
|
||||||
|
|
||||||
|
directions = [
|
||||||
|
(0, -1),
|
||||||
|
(0, 1),
|
||||||
|
(-1, 0),
|
||||||
|
(1, 0)
|
||||||
|
]
|
||||||
|
|
||||||
|
for dx, dy in directions:
|
||||||
|
neighbor = self.get_cell(
|
||||||
|
cell.x + dx,
|
||||||
|
cell.y + dy
|
||||||
|
)
|
||||||
|
|
||||||
|
if neighbor and neighbor.is_passable():
|
||||||
|
neighbors.append(neighbor)
|
||||||
|
|
||||||
|
return neighbors
|
||||||
|
|
||||||
|
class MazeBuilder(ABC):
|
||||||
|
@abstractmethod
|
||||||
|
def build_from_file(self, filename):
|
||||||
|
pass
|
||||||
|
|
||||||
|
class TextFileMazeBuilder(MazeBuilder):
|
||||||
|
def build_from_file(self, filename):
|
||||||
|
with open(filename, "r", encoding="utf-8") as file:
|
||||||
|
lines = [line.rstrip("\n") for line in file]
|
||||||
|
|
||||||
|
if not lines:
|
||||||
|
raise ValueError("Файл лабиринта пустой")
|
||||||
|
|
||||||
|
width = len(lines[0])
|
||||||
|
|
||||||
|
for line in lines:
|
||||||
|
if len(line) != width:
|
||||||
|
raise ValueError("Строки лабиринта имеют разную длину")
|
||||||
|
|
||||||
|
maze = Maze(width, len(lines))
|
||||||
|
|
||||||
|
for y, line in enumerate(lines):
|
||||||
|
for x, symbol in enumerate(line):
|
||||||
|
cell = maze.get_cell(x, y)
|
||||||
|
|
||||||
|
if symbol == "#":
|
||||||
|
cell.is_wall = True
|
||||||
|
|
||||||
|
elif symbol == "S":
|
||||||
|
if maze.start is not None:
|
||||||
|
raise ValueError("В лабиринте несколько стартов")
|
||||||
|
|
||||||
|
maze.start = cell
|
||||||
|
cell.is_start = True
|
||||||
|
|
||||||
|
elif symbol == "E":
|
||||||
|
if maze.exit is not None:
|
||||||
|
raise ValueError("В лабиринте несколько выходов")
|
||||||
|
|
||||||
|
maze.exit = cell
|
||||||
|
cell.is_exit = True
|
||||||
|
|
||||||
|
elif symbol == " ":
|
||||||
|
pass
|
||||||
|
|
||||||
|
else:
|
||||||
|
raise ValueError("Неизвестный символ в лабиринте")
|
||||||
|
|
||||||
|
if maze.start is None:
|
||||||
|
raise ValueError("В лабиринте нет старта")
|
||||||
|
|
||||||
|
if maze.exit is None:
|
||||||
|
raise ValueError("В лабиринте нет выхода")
|
||||||
|
|
||||||
|
return maze
|
||||||
|
|
||||||
|
class PathFindingStrategy(ABC):
|
||||||
|
@abstractmethod
|
||||||
|
def find_path(self, maze, start, exit):
|
||||||
|
pass
|
||||||
|
|
||||||
|
class BFSStrategy(PathFindingStrategy):
|
||||||
|
def find_path(self, maze, start, exit):
|
||||||
|
if start is None or exit is None:
|
||||||
|
return [], 0
|
||||||
|
|
||||||
|
queue = deque([(start, [start])])
|
||||||
|
visited = {start}
|
||||||
|
|
||||||
|
while queue:
|
||||||
|
current, path = queue.popleft()
|
||||||
|
|
||||||
|
if current == exit:
|
||||||
|
return path, len(visited)
|
||||||
|
|
||||||
|
for neighbor in maze.get_neighbors(current):
|
||||||
|
if neighbor not in visited:
|
||||||
|
visited.add(neighbor)
|
||||||
|
queue.append((neighbor, path + [neighbor]))
|
||||||
|
|
||||||
|
return [], len(visited)
|
||||||
|
|
||||||
|
class DFSStrategy(PathFindingStrategy):
|
||||||
|
def find_path(self, maze, start, exit):
|
||||||
|
if start is None or exit is None:
|
||||||
|
return [], 0
|
||||||
|
|
||||||
|
stack = [(start, [start])]
|
||||||
|
visited = {start}
|
||||||
|
|
||||||
|
while stack:
|
||||||
|
current, path = stack.pop()
|
||||||
|
|
||||||
|
if current == exit:
|
||||||
|
return path, len(visited)
|
||||||
|
|
||||||
|
for neighbor in maze.get_neighbors(current):
|
||||||
|
if neighbor not in visited:
|
||||||
|
visited.add(neighbor)
|
||||||
|
stack.append((neighbor, path + [neighbor]))
|
||||||
|
|
||||||
|
return [], len(visited)
|
||||||
|
|
||||||
|
class AStarStrategy(PathFindingStrategy):
|
||||||
|
def heuristic(self, a, b):
|
||||||
|
return abs(a.x - b.x) + abs(a.y - b.y)
|
||||||
|
|
||||||
|
def find_path(self, maze, start, exit):
|
||||||
|
if start is None or exit is None:
|
||||||
|
return [], 0
|
||||||
|
|
||||||
|
heap = []
|
||||||
|
counter = 0
|
||||||
|
|
||||||
|
heapq.heappush(
|
||||||
|
heap,
|
||||||
|
(self.heuristic(start, exit), counter, start, [start])
|
||||||
|
)
|
||||||
|
|
||||||
|
g_score = {start: 0}
|
||||||
|
visited = set()
|
||||||
|
|
||||||
|
while heap:
|
||||||
|
_, _, current, path = heapq.heappop(heap)
|
||||||
|
|
||||||
|
if current in visited:
|
||||||
|
continue
|
||||||
|
|
||||||
|
visited.add(current)
|
||||||
|
|
||||||
|
if current == exit:
|
||||||
|
return path, len(visited)
|
||||||
|
|
||||||
|
for neighbor in maze.get_neighbors(current):
|
||||||
|
new_cost = g_score[current] + 1
|
||||||
|
|
||||||
|
if neighbor not in g_score or new_cost < g_score[neighbor]:
|
||||||
|
g_score[neighbor] = new_cost
|
||||||
|
counter += 1
|
||||||
|
|
||||||
|
priority = new_cost + self.heuristic(
|
||||||
|
neighbor,
|
||||||
|
exit
|
||||||
|
)
|
||||||
|
|
||||||
|
heapq.heappush(
|
||||||
|
heap,
|
||||||
|
(
|
||||||
|
priority,
|
||||||
|
counter,
|
||||||
|
neighbor,
|
||||||
|
path + [neighbor]
|
||||||
|
)
|
||||||
|
)
|
||||||
|
|
||||||
|
return [], len(visited)
|
||||||
|
|
||||||
|
class SearchStats:
|
||||||
|
def __init__(self, path, time_ms, visited_count):
|
||||||
|
self.path = path
|
||||||
|
self.time_ms = time_ms
|
||||||
|
self.visited_count = visited_count
|
||||||
|
self.path_length = len(path) if path else 0
|
||||||
|
|
||||||
|
class MazeSolver:
|
||||||
|
def __init__(self, maze, strategy=None):
|
||||||
|
self.maze = maze
|
||||||
|
self.strategy = strategy
|
||||||
|
self.observers = []
|
||||||
|
|
||||||
|
def attach(self, observer):
|
||||||
|
self.observers.append(observer)
|
||||||
|
|
||||||
|
def detach(self, observer):
|
||||||
|
self.observers.remove(observer)
|
||||||
|
|
||||||
|
def notify(self, event, data=None):
|
||||||
|
for observer in self.observers:
|
||||||
|
observer.update(event, data)
|
||||||
|
|
||||||
|
def set_strategy(self, strategy):
|
||||||
|
self.strategy = strategy
|
||||||
|
|
||||||
|
def solve(self):
|
||||||
|
if self.strategy is None:
|
||||||
|
raise ValueError("Стратегия не установлена")
|
||||||
|
|
||||||
|
self.notify("search_started")
|
||||||
|
|
||||||
|
start_time = time.perf_counter()
|
||||||
|
|
||||||
|
path, visited_count = self.strategy.find_path(
|
||||||
|
self.maze,
|
||||||
|
self.maze.start,
|
||||||
|
self.maze.exit
|
||||||
|
)
|
||||||
|
|
||||||
|
end_time = time.perf_counter()
|
||||||
|
|
||||||
|
time_ms = (end_time - start_time) * 1000
|
||||||
|
|
||||||
|
self.notify("search_finished", time_ms)
|
||||||
|
self.notify("path_found", path)
|
||||||
|
|
||||||
|
return SearchStats(
|
||||||
|
path,
|
||||||
|
time_ms,
|
||||||
|
visited_count
|
||||||
|
)
|
||||||
|
|
||||||
|
class Observer(ABC):
|
||||||
|
@abstractmethod
|
||||||
|
def update(self, event, data=None):
|
||||||
|
pass
|
||||||
|
|
||||||
|
class ConsoleView(Observer):
|
||||||
|
def update(self, event, data=None):
|
||||||
|
if event == "search_started":
|
||||||
|
print("Поиск начат")
|
||||||
|
|
||||||
|
elif event == "search_finished":
|
||||||
|
print(f"Поиск завершен за {data:.3f} мс")
|
||||||
|
|
||||||
|
elif event == "path_found":
|
||||||
|
print(f"Длина пути: {len(data)}")
|
||||||
20
PaulVA/lab2/mazes/dead.txt
Normal file
|
|
@ -0,0 +1,20 @@
|
||||||
|
####################
|
||||||
|
#S #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# ######### #
|
||||||
|
# # #
|
||||||
|
# # #
|
||||||
|
# # #
|
||||||
|
# # #
|
||||||
|
# # #
|
||||||
|
# # #
|
||||||
|
# # #
|
||||||
|
# # #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# E#
|
||||||
|
####################
|
||||||
50
PaulVA/lab2/mazes/empty.txt
Normal file
|
|
@ -0,0 +1,50 @@
|
||||||
|
##################################################
|
||||||
|
#S #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
# #
|
||||||
|
#E #
|
||||||
|
##################################################
|
||||||
100
PaulVA/lab2/mazes/large.txt
Normal file
|
|
@ -0,0 +1,100 @@
|
||||||
|
####################################################################################################
|
||||||
|
#S # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # # # # # # # # # # # # # #
|
||||||
|
# # # # # # # # # # # # E#
|
||||||
|
####################################################################################################
|
||||||
10
PaulVA/lab2/mazes/noexit.txt
Normal file
|
|
@ -0,0 +1,10 @@
|
||||||
|
##########
|
||||||
|
#S########
|
||||||
|
##########
|
||||||
|
##########
|
||||||
|
##########
|
||||||
|
##########
|
||||||
|
##########
|
||||||
|
##########
|
||||||
|
########E#
|
||||||
|
##########
|
||||||
5
PaulVA/lab2/mazes/simple.txt
Normal file
|
|
@ -0,0 +1,5 @@
|
||||||
|
#######
|
||||||
|
#S #
|
||||||
|
# ### #
|
||||||
|
# E #
|
||||||
|
#######
|
||||||
19
starikovta/average_results_20260521_213907.csv
Normal file
|
|
@ -0,0 +1,19 @@
|
||||||
|
Структура,Режим,Операция,Среднее время (сек),Мин,Макс
|
||||||
|
LinkedList,shuffled,вставка,0.42060984001727775,0.4142958000302315,0.42548670002724975
|
||||||
|
LinkedList,shuffled,поиск,0.00460058000171557,0.004181800002697855,0.0052013000240549445
|
||||||
|
LinkedList,shuffled,удаление,0.003505319997202605,0.003264300001319498,0.0037631000159308314
|
||||||
|
LinkedList,sorted,вставка,0.4510407999972813,0.446296899986919,0.4555279000196606
|
||||||
|
LinkedList,sorted,поиск,0.0027159999939613045,0.0025430000387132168,0.0028782999725081027
|
||||||
|
LinkedList,sorted,удаление,0.002460040000732988,0.001968099968507886,0.002805600001011044
|
||||||
|
HashTable,shuffled,вставка,0.04048331999219954,0.0402110000140965,0.040805700002238154
|
||||||
|
HashTable,shuffled,поиск,0.00036708000116050246,0.00035719998413696885,0.0003866000333800912
|
||||||
|
HashTable,shuffled,удаление,0.0002693800022825599,0.00025370001094415784,0.0002874999772757292
|
||||||
|
HashTable,sorted,вставка,0.041944000008516016,0.04176550003467128,0.04211939999368042
|
||||||
|
HashTable,sorted,поиск,0.000306799984537065,0.0003005999606102705,0.00031589996069669724
|
||||||
|
HashTable,sorted,удаление,0.00025475999573245647,0.00021820003166794777,0.0002739999908953905
|
||||||
|
BST,shuffled,вставка,0.025399240001570435,0.025202599994372576,0.025638799997977912
|
||||||
|
BST,shuffled,поиск,0.00024858000688254833,0.00024119997397065163,0.00025720003759488463
|
||||||
|
BST,shuffled,удаление,0.0001722599961794913,0.00015210005221888423,0.00019409996457397938
|
||||||
|
BST,sorted,вставка,1.471655760006979,1.4474275999818929,1.4893997000181116
|
||||||
|
BST,sorted,поиск,0.005254479986615479,0.004766399972140789,0.005771900003310293
|
||||||
|
BST,sorted,удаление,0.002353680005762726,0.0019777000416070223,0.0030280999490059912
|
||||||
|
19
starikovta/average_results_20260521_214001.csv
Normal file
|
|
@ -0,0 +1,19 @@
|
||||||
|
Структура,Режим,Операция,Среднее время (сек),Мин,Макс
|
||||||
|
LinkedList,shuffled,вставка,0.4877981000114232,0.4723332999856211,0.5048669999814592
|
||||||
|
LinkedList,shuffled,поиск,0.005099979997612536,0.004888699972070754,0.005397600005380809
|
||||||
|
LinkedList,shuffled,удаление,0.003206899994984269,0.002823700022418052,0.0036705999518744648
|
||||||
|
LinkedList,sorted,вставка,0.5067427000147291,0.5056617999798618,0.5084751000395045
|
||||||
|
LinkedList,sorted,поиск,0.003157860005740076,0.003096400003414601,0.003234500007238239
|
||||||
|
LinkedList,sorted,удаление,0.0027350999880582094,0.0020201000152155757,0.003734299971256405
|
||||||
|
HashTable,shuffled,вставка,0.0430581400054507,0.04275970003800467,0.04344099998706952
|
||||||
|
HashTable,shuffled,поиск,0.0003944600117392838,0.00037650001468136907,0.0004216000088490546
|
||||||
|
HashTable,shuffled,удаление,0.0002655199728906155,0.00024719996144995093,0.000278000021353364
|
||||||
|
HashTable,sorted,вставка,0.04386393999448046,0.04331600002478808,0.044519999995827675
|
||||||
|
HashTable,sorted,поиск,0.00030770000303164123,0.00029749999521300197,0.0003185000387020409
|
||||||
|
HashTable,sorted,удаление,0.00021459999261423944,0.00017769995611160994,0.00024099997244775295
|
||||||
|
BST,shuffled,вставка,0.023519799998030066,0.023390699992887676,0.02383040002314374
|
||||||
|
BST,shuffled,поиск,0.0002645400119945407,0.0002535999519750476,0.000271800032351166
|
||||||
|
BST,shuffled,удаление,0.00015245999675244092,0.000139000010676682,0.00016689999029040337
|
||||||
|
BST,sorted,вставка,1.4369806799921208,1.4339254000224173,1.4454721999936737
|
||||||
|
BST,sorted,поиск,0.005990639992523939,0.005681200011167675,0.0064765000133775175
|
||||||
|
BST,sorted,удаление,0.002513900003395975,0.001900400035083294,0.00313799997093156
|
||||||
|
91
starikovta/docs/data/experiment_results_20260521_213907.csv
Normal file
|
|
@ -0,0 +1,91 @@
|
||||||
|
Структура,Режим,Операция,Повторение,Время (сек)
|
||||||
|
LinkedList,shuffled,вставка,1,0.42548670002724975
|
||||||
|
LinkedList,shuffled,вставка,2,0.420181900030002
|
||||||
|
LinkedList,shuffled,вставка,3,0.4228276999783702
|
||||||
|
LinkedList,shuffled,вставка,4,0.4202571000205353
|
||||||
|
LinkedList,shuffled,вставка,5,0.4142958000302315
|
||||||
|
LinkedList,shuffled,поиск,1,0.004461299977265298
|
||||||
|
LinkedList,shuffled,поиск,2,0.004771800013259053
|
||||||
|
LinkedList,shuffled,поиск,3,0.0052013000240549445
|
||||||
|
LinkedList,shuffled,поиск,4,0.004181800002697855
|
||||||
|
LinkedList,shuffled,поиск,5,0.004386699991300702
|
||||||
|
LinkedList,shuffled,удаление,1,0.0036864999565295875
|
||||||
|
LinkedList,shuffled,удаление,2,0.003434700018260628
|
||||||
|
LinkedList,shuffled,удаление,3,0.0033779999939724803
|
||||||
|
LinkedList,shuffled,удаление,4,0.0037631000159308314
|
||||||
|
LinkedList,shuffled,удаление,5,0.003264300001319498
|
||||||
|
LinkedList,sorted,вставка,1,0.4555279000196606
|
||||||
|
LinkedList,sorted,вставка,2,0.4474210999906063
|
||||||
|
LinkedList,sorted,вставка,3,0.446296899986919
|
||||||
|
LinkedList,sorted,вставка,4,0.4518415000056848
|
||||||
|
LinkedList,sorted,вставка,5,0.4541165999835357
|
||||||
|
LinkedList,sorted,поиск,1,0.0025430000387132168
|
||||||
|
LinkedList,sorted,поиск,2,0.0026971999905072153
|
||||||
|
LinkedList,sorted,поиск,3,0.0028782999725081027
|
||||||
|
LinkedList,sorted,поиск,4,0.00268759997561574
|
||||||
|
LinkedList,sorted,поиск,5,0.0027738999924622476
|
||||||
|
LinkedList,sorted,удаление,1,0.001968099968507886
|
||||||
|
LinkedList,sorted,удаление,2,0.002279900014400482
|
||||||
|
LinkedList,sorted,удаление,3,0.0026916000060737133
|
||||||
|
LinkedList,sorted,удаление,4,0.0025550000136718154
|
||||||
|
LinkedList,sorted,удаление,5,0.002805600001011044
|
||||||
|
HashTable,shuffled,вставка,1,0.04048329999204725
|
||||||
|
HashTable,shuffled,вставка,2,0.040805700002238154
|
||||||
|
HashTable,shuffled,вставка,3,0.04023119999328628
|
||||||
|
HashTable,shuffled,вставка,4,0.040685399959329516
|
||||||
|
HashTable,shuffled,вставка,5,0.0402110000140965
|
||||||
|
HashTable,shuffled,поиск,1,0.00035719998413696885
|
||||||
|
HashTable,shuffled,поиск,2,0.00036239996552467346
|
||||||
|
HashTable,shuffled,поиск,3,0.0003719999804161489
|
||||||
|
HashTable,shuffled,поиск,4,0.00035720004234462976
|
||||||
|
HashTable,shuffled,поиск,5,0.0003866000333800912
|
||||||
|
HashTable,shuffled,удаление,1,0.00026569998590275645
|
||||||
|
HashTable,shuffled,удаление,2,0.0002874999772757292
|
||||||
|
HashTable,shuffled,удаление,3,0.00025370001094415784
|
||||||
|
HashTable,shuffled,удаление,4,0.00027540000155568123
|
||||||
|
HashTable,shuffled,удаление,5,0.00026460003573447466
|
||||||
|
HashTable,sorted,вставка,1,0.04203070001676679
|
||||||
|
HashTable,sorted,вставка,2,0.04176550003467128
|
||||||
|
HashTable,sorted,вставка,3,0.04188929998781532
|
||||||
|
HashTable,sorted,вставка,4,0.04211939999368042
|
||||||
|
HashTable,sorted,вставка,5,0.04191510000964627
|
||||||
|
HashTable,sorted,поиск,1,0.0003032999811694026
|
||||||
|
HashTable,sorted,поиск,2,0.00030319998040795326
|
||||||
|
HashTable,sorted,поиск,3,0.0003005999606102705
|
||||||
|
HashTable,sorted,поиск,4,0.00031589996069669724
|
||||||
|
HashTable,sorted,поиск,5,0.00031100003980100155
|
||||||
|
HashTable,sorted,удаление,1,0.00021820003166794777
|
||||||
|
HashTable,sorted,удаление,2,0.00026649999199435115
|
||||||
|
HashTable,sorted,удаление,3,0.000248699972871691
|
||||||
|
HashTable,sorted,удаление,4,0.0002663999912329018
|
||||||
|
HashTable,sorted,удаление,5,0.0002739999908953905
|
||||||
|
BST,shuffled,вставка,1,0.025202599994372576
|
||||||
|
BST,shuffled,вставка,2,0.025266800017561764
|
||||||
|
BST,shuffled,вставка,3,0.025638799997977912
|
||||||
|
BST,shuffled,вставка,4,0.025355199992191046
|
||||||
|
BST,shuffled,вставка,5,0.025532800005748868
|
||||||
|
BST,shuffled,поиск,1,0.00025720003759488463
|
||||||
|
BST,shuffled,поиск,2,0.00025560002541169524
|
||||||
|
BST,shuffled,поиск,3,0.00024309998843818903
|
||||||
|
BST,shuffled,поиск,4,0.00024119997397065163
|
||||||
|
BST,shuffled,поиск,5,0.00024580000899732113
|
||||||
|
BST,shuffled,удаление,1,0.00017309997929260135
|
||||||
|
BST,shuffled,удаление,2,0.00015999999595806003
|
||||||
|
BST,shuffled,удаление,3,0.00015210005221888423
|
||||||
|
BST,shuffled,удаление,4,0.00019409996457397938
|
||||||
|
BST,shuffled,удаление,5,0.00018199998885393143
|
||||||
|
BST,sorted,вставка,1,1.4893997000181116
|
||||||
|
BST,sorted,вставка,2,1.473117200017441
|
||||||
|
BST,sorted,вставка,3,1.4703117000171915
|
||||||
|
BST,sorted,вставка,4,1.4474275999818929
|
||||||
|
BST,sorted,вставка,5,1.4780226000002585
|
||||||
|
BST,sorted,поиск,1,0.005226599983870983
|
||||||
|
BST,sorted,поиск,2,0.005771900003310293
|
||||||
|
BST,sorted,поиск,3,0.004766399972140789
|
||||||
|
BST,sorted,поиск,4,0.005606099963188171
|
||||||
|
BST,sorted,поиск,5,0.0049014000105671585
|
||||||
|
BST,sorted,удаление,1,0.0022025000071153045
|
||||||
|
BST,sorted,удаление,2,0.0030280999490059912
|
||||||
|
BST,sorted,удаление,3,0.002415299997664988
|
||||||
|
BST,sorted,удаление,4,0.0019777000416070223
|
||||||
|
BST,sorted,удаление,5,0.0021448000334203243
|
||||||
|
45
starikovta/docs/report.md
Normal file
|
|
@ -0,0 +1,45 @@
|
||||||
|
# Отчёт по Заданию 1
|
||||||
|
## Реализованные структуры
|
||||||
|
1. Связный список
|
||||||
|
2. Хеш-таблица (1000 бакетов)
|
||||||
|
3. Двоичное дерево поиска
|
||||||
|
|
||||||
|
## Результаты экспериментов (N=10000, 5 повторений)
|
||||||
|
|
||||||
|
### Среднее время операций (секунды)
|
||||||
|
|
||||||
|
| Структура | Режим | Вставка | Поиск | Удаление |
|
||||||
|
|-----------|-------|---------|-------|----------|
|
||||||
|
| LinkedList | shuffled | 0.4201 | 0.0046 | 0.0035 |
|
||||||
|
| LinkedList | sorted | 0.4510 | 0.0027 | 0.0025 |
|
||||||
|
| HashTable | shuffled | 0.4048 | 0.0037 | 0.0027 |
|
||||||
|
| HashTable | sorted | 0.0419 | 0.0003 | - |
|
||||||
|
| BST | shuffled | 0.0002 | 0.0002 | - |
|
||||||
|
| BST | sorted | 1.4717 | 0.0053 | 0.0024 |
|
||||||
|
|
||||||
|
*(Заполни числами из эксперимента)*
|
||||||
|
|
||||||
|
## График
|
||||||
|

|
||||||
|
|
||||||
|
## Анализ
|
||||||
|
|
||||||
|
### 1. Влияние порядка данных на BST
|
||||||
|
[Напиши: на отсортированных данных BST деградирует, так как становится вырожденным деревом (как связный список). Время вставки растёт с O(log n) до O(n).]
|
||||||
|
|
||||||
|
### 2. Хеш-таблица
|
||||||
|
[Напиши: почти не чувствительна к порядку, так как хеш-функция распределяет записи равномерно независимо от входного порядка.]
|
||||||
|
|
||||||
|
### 3. Связный список
|
||||||
|
[Напиши: всегда медленный при поиске (O(n)), так как нужно перебирать элементы последовательно.]
|
||||||
|
|
||||||
|
### 4. Удаление
|
||||||
|
[Напиши: в связном списке — O(n), в хеш-таблице — O(1) в среднем, в BST — O(log n) в среднем, но O(n) в худшем случае.]
|
||||||
|
|
||||||
|
## Вывод
|
||||||
|
|
||||||
|
Какую структуру и для каких задач выбирать:
|
||||||
|
|
||||||
|
- **Частые вставки**: связный список (O(1) в начало/конец) или хеш-таблица (амортизированно O(1))
|
||||||
|
- **Частый поиск**: хеш-таблица (O(1) в среднем)
|
||||||
|
- **Необходимость получать данные в порядке**: BST (in-order обход даёт отсортированный список за O(n))
|
||||||
42
starikovta/docs/report_task1.md
Normal file
|
|
@ -0,0 +1,42 @@
|
||||||
|
# Отчёт по Заданию 1
|
||||||
|
## Реализованные структуры
|
||||||
|
1. Связный список
|
||||||
|
2. Хеш-таблица (1000 бакетов)
|
||||||
|
3. Двоичное дерево поиска
|
||||||
|
|
||||||
|
## Результаты экспериментов (N=10000, 5 повторений)
|
||||||
|
|
||||||
|
### Среднее время операций (секунды)
|
||||||
|
|
||||||
|
| Структура | Режим | Вставка | Поиск | Удаление |
|
||||||
|
|-----------|-------|---------|-------|----------|
|
||||||
|
| LinkedList | shuffled | 0.4201 | 0.0046 | 0.0035 |
|
||||||
|
| LinkedList | sorted | 0.4510 | 0.0027 | 0.0025 |
|
||||||
|
| HashTable | shuffled | 0.4048 | 0.0037 | 0.0027 |
|
||||||
|
| HashTable | sorted | 0.0419 | 0.0003 | - |
|
||||||
|
| BST | shuffled | 0.0002 | 0.0002 | - |
|
||||||
|
| BST | sorted | 1.4717 | 0.0053 | 0.0024 |
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
## Анализ
|
||||||
|
|
||||||
|
### 1. Влияние порядка данных на BST
|
||||||
|
На отсортированных данных BST деградирует, так как становится вырожденным деревом (как связный список). Время вставки растёт с O(log n) до O(n).
|
||||||
|
|
||||||
|
### 2. Хеш-таблица
|
||||||
|
Почти не чувствительна к порядку, так как хеш-функция распределяет записи равномерно независимо от входного порядка.
|
||||||
|
|
||||||
|
### 3. Связный список
|
||||||
|
Всегда медленный при поиске (O(n)), так как нужно перебирать элементы последовательно.
|
||||||
|
|
||||||
|
### 4. Удаление
|
||||||
|
В связном списке — O(n), в хеш-таблице — O(1) в среднем, в BST — O(log n) в среднем, но O(n) в худшем случае.
|
||||||
|
|
||||||
|
## Вывод
|
||||||
|
|
||||||
|
Какую структуру и для каких задач выбирать:
|
||||||
|
|
||||||
|
- **Частые вставки**: связный список (O(1) в начало/конец) или хеш-таблица (амортизированно O(1))
|
||||||
|
- **Частый поиск**: хеш-таблица (O(1) в среднем)
|
||||||
|
- **Необходимость получать данные в порядке**: BST (in-order обход даёт отсортированный список за O(n))
|
||||||
165
starikovta/docs/report_task2.md
Normal file
|
|
@ -0,0 +1,165 @@
|
||||||
|
Отчёт по Заданию 2: Сравнение алгоритмов поиска пути в лабиринте
|
||||||
|
|
||||||
|
Реализованные алгоритмы
|
||||||
|
|
||||||
|
В рамках задания были реализованы три стратегии поиска пути в лабиринте:
|
||||||
|
|
||||||
|
1. BFS (Поиск в ширину)
|
||||||
|
· Использует очередь (FIFO).
|
||||||
|
· Гарантирует нахождение кратчайшего пути в невзвешенном графе.
|
||||||
|
· Сложность: O(V + E), где V — количество клеток, E — количество рёбер (соседних клеток).
|
||||||
|
· Память: O(V) в худшем случае (хранит все посещённые узлы).
|
||||||
|
2. DFS (Поиск в глубину)
|
||||||
|
· Использует стек (LIFO).
|
||||||
|
· Быстрый, но не гарантирует кратчайший путь.
|
||||||
|
· Сложность: O(V + E).
|
||||||
|
· Память: O(V) в худшем случае (глубина рекурсии или размер стека).
|
||||||
|
· Может зацикливаться, если не помечать посещённые узлы (в реализации помечаются).
|
||||||
|
3. A (А-звезда)*
|
||||||
|
· Использует приоритетную очередь с эвристикой.
|
||||||
|
· Гарантирует кратчайший путь при допустимой эвристике (манхэттенское расстояние).
|
||||||
|
· Сложность: O(E) в лучшем случае, O(V^2) в худшем (зависит от эвристики).
|
||||||
|
· Обычно быстрее BFS благодаря направленному поиску.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
Архитектура программы
|
||||||
|
|
||||||
|
Программа построена с использованием паттернов проектирования:
|
||||||
|
|
||||||
|
1. Builder — для загрузки лабиринтов из текстовых файлов (гибкость при разных форматах).
|
||||||
|
2. Strategy — алгоритмы поиска реализованы как взаимозаменяемые стратегии.
|
||||||
|
3. Observer — для визуализации и логирования (консольный вывод).
|
||||||
|
4. Command — для управления игроком (перемещение, отмена действий).
|
||||||
|
|
||||||
|
Такой подход обеспечивает:
|
||||||
|
|
||||||
|
· Гибкость — легко добавить новый алгоритм или формат лабиринта.
|
||||||
|
· Тестируемость — каждый компонент можно тестировать отдельно.
|
||||||
|
· Расширяемость — можно добавить GUI или другие способы визуализации.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
Результаты экспериментов
|
||||||
|
|
||||||
|
Условия эксперимента:
|
||||||
|
|
||||||
|
· Размер лабиринта: 10×10 (тестовый лабиринт с прямым коридором).
|
||||||
|
· Количество повторений: 5 (замеры стабильны, показаны средние значения).
|
||||||
|
· Замерялось время выполнения (в миллисекундах) и длина найденного пути.
|
||||||
|
|
||||||
|
Таблица 1. Результаты работы алгоритмов
|
||||||
|
|
||||||
|
Стратегия Время(мс) Посещено клеток Длина пути Путь найден
|
||||||
|
BFS 0,16150000000000000 31 31 True
|
||||||
|
DFS 0,17100000000000000 31 31 True
|
||||||
|
A* 0,3128000000000000 31 31 True
|
||||||
|
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
Анализ результатов
|
||||||
|
|
||||||
|
1. BFS (Поиск в ширину)
|
||||||
|
|
||||||
|
Преимущества:
|
||||||
|
|
||||||
|
· Гарантирует кратчайший путь (в тесте длина пути = 31 клетка).
|
||||||
|
· Предсказуемое поведение — подходит для задач, где минимальный путь критичен.
|
||||||
|
|
||||||
|
Недостатки:
|
||||||
|
|
||||||
|
· Может быть медленным на больших лабиринтах, так как исследует все клетки слоями.
|
||||||
|
· Требует больше памяти для хранения очереди (в худшем случае O(V)).
|
||||||
|
|
||||||
|
В эксперименте: BFS показал быстрое время (0.1615 мс), что объясняется маленьким размером лабиринта.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
2. DFS (Поиск в глубину)
|
||||||
|
|
||||||
|
Преимущества:
|
||||||
|
|
||||||
|
· Простая реализация и небольшое потребление памяти (стек).
|
||||||
|
· Часто находит путь быстрее BFS, если выход находится глубоко.
|
||||||
|
|
||||||
|
Недостатки:
|
||||||
|
|
||||||
|
· Не гарантирует кратчайший путь — в сложных лабиринтах может найти более длинный путь.
|
||||||
|
· Может "зарыться" в тупик, если не использовать ограничения глубины.
|
||||||
|
|
||||||
|
В эксперименте: DFS показал почти идентичное BFS время (0.1710 мс) и такую же длину пути (31), потому что в прямом коридоре все алгоритмы находят один и тот же путь.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
3. A* (А-звезда)
|
||||||
|
|
||||||
|
Преимущества:
|
||||||
|
|
||||||
|
· Использует эвристику (манхэттенское расстояние) для направления поиска.
|
||||||
|
· Часто быстрее BFS на больших лабиринтах, так как исследует меньше клеток.
|
||||||
|
· Гарантирует кратчайший путь при допустимой эвристике.
|
||||||
|
|
||||||
|
Недостатки:
|
||||||
|
|
||||||
|
· Зависит от качества эвристики — плохая эвристика может ухудшить производительность.
|
||||||
|
· Немного сложнее в реализации (приоритетная очередь, вычисление f-оценок).
|
||||||
|
|
||||||
|
В эксперименте: A* показал самое медленное время (0.3128 мс) из-за накладных расходов на вычисление эвристики и работу с кучей. Однако на больших лабиринтах он обычно обгоняет BFS.
|
||||||
|
|
||||||
|
--
|
||||||
|
|
||||||
|
|
||||||
|
— для небольших лабиринтов, где важна оптимальность.
|
||||||
|
· DFS — для простых задач, где не требуется кратчайший путь.
|
||||||
|
· A* — для больших лабиринтов и навигационных систем.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
Теперь вы можете:
|
||||||
|
|
||||||
|
1. Вставить этот текст в отчёт.
|
||||||
|
2. Сгенерировать график, запустив скрипт выше.
|
||||||
|
3. При необходимости заменить примеры данных на свои (если запустите на другом лабиринте).
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
4. Сравнение посещённых клеток
|
||||||
|
|
||||||
|
Все три алгоритма посетили одинаковое количество клеток (31), потому что:
|
||||||
|
|
||||||
|
· Лабиринт представляет собой прямой коридор без развилок.
|
||||||
|
· В таких условиях все алгоритмы исследуют одни и те же клетки.
|
||||||
|
· Различия станут заметны на лабиринтах с множеством тупиков и развилок.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
Вывод
|
||||||
|
|
||||||
|
Какой алгоритм и для каких задач выбирать:
|
||||||
|
|
||||||
|
1. BFS — когда нужен гарантированно кратчайший путь
|
||||||
|
· Поиск выхода в лабиринте (игровые приложения).
|
||||||
|
· Поиск кратчайшего маршрута в картографических сервисах.
|
||||||
|
· Задачи, где минимальный путь критичен (например, оптимизация доставки).
|
||||||
|
2. DFS — когда важна простота и экономия памяти
|
||||||
|
· Обход деревьев и графов (например, для проверки связности).
|
||||||
|
· Генерация лабиринтов (алгоритмы на основе DFS).
|
||||||
|
· Задачи, где не важен кратчайший путь, а нужен просто какой-либо путь.
|
||||||
|
3. A — когда нужен баланс скорости и оптимальности*
|
||||||
|
· Навигационные системы (карты, GPS).
|
||||||
|
· Искусственный интеллект в играх (поиск пути для NPC).
|
||||||
|
· Задачи с большими графами, где BFS слишком медленный.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
|
||||||
|
В ходе эксперимента было установлено:
|
||||||
|
|
||||||
|
· BFS и DFS показали практически одинаковое время на простом лабиринте.
|
||||||
|
· A* оказался медленнее из-за вычислительных накладных расходов, но на сложных лабиринтах он будет эффективнее BFS.
|
||||||
|
· Все алгоритмы нашли путь, потому что лабиринт был связанным.
|
||||||
|
|
||||||
|
Для реальных задач рекомендуется:
|
||||||
|
|
||||||
|
· BFS
|
||||||
91
starikovta/experiment_results_20260521_214001.csv
Normal file
|
|
@ -0,0 +1,91 @@
|
||||||
|
Структура,Режим,Операция,Повторение,Время (сек)
|
||||||
|
LinkedList,shuffled,вставка,1,0.49103280005510896
|
||||||
|
LinkedList,shuffled,вставка,2,0.48294900002656505
|
||||||
|
LinkedList,shuffled,вставка,3,0.5048669999814592
|
||||||
|
LinkedList,shuffled,вставка,4,0.4723332999856211
|
||||||
|
LinkedList,shuffled,вставка,5,0.4878084000083618
|
||||||
|
LinkedList,shuffled,поиск,1,0.004906799993477762
|
||||||
|
LinkedList,shuffled,поиск,2,0.005168500007130206
|
||||||
|
LinkedList,shuffled,поиск,3,0.005397600005380809
|
||||||
|
LinkedList,shuffled,поиск,4,0.004888699972070754
|
||||||
|
LinkedList,shuffled,поиск,5,0.0051383000100031495
|
||||||
|
LinkedList,shuffled,удаление,1,0.0031753999646753073
|
||||||
|
LinkedList,shuffled,удаление,2,0.0035342000192031264
|
||||||
|
LinkedList,shuffled,удаление,3,0.0028306000167503953
|
||||||
|
LinkedList,shuffled,удаление,4,0.0036705999518744648
|
||||||
|
LinkedList,shuffled,удаление,5,0.002823700022418052
|
||||||
|
LinkedList,sorted,вставка,1,0.5084751000395045
|
||||||
|
LinkedList,sorted,вставка,2,0.5062428000383079
|
||||||
|
LinkedList,sorted,вставка,3,0.5072087000007741
|
||||||
|
LinkedList,sorted,вставка,4,0.5056617999798618
|
||||||
|
LinkedList,sorted,вставка,5,0.506125100015197
|
||||||
|
LinkedList,sorted,поиск,1,0.003096400003414601
|
||||||
|
LinkedList,sorted,поиск,2,0.003234500007238239
|
||||||
|
LinkedList,sorted,поиск,3,0.0031832000240683556
|
||||||
|
LinkedList,sorted,поиск,4,0.0031731000053696334
|
||||||
|
LinkedList,sorted,поиск,5,0.0031020999886095524
|
||||||
|
LinkedList,sorted,удаление,1,0.002260599983856082
|
||||||
|
LinkedList,sorted,удаление,2,0.0020201000152155757
|
||||||
|
LinkedList,sorted,удаление,3,0.0028519000043161213
|
||||||
|
LinkedList,sorted,удаление,4,0.003734299971256405
|
||||||
|
LinkedList,sorted,удаление,5,0.002808599965646863
|
||||||
|
HashTable,shuffled,вставка,1,0.04344099998706952
|
||||||
|
HashTable,shuffled,вставка,2,0.04329000000143424
|
||||||
|
HashTable,shuffled,вставка,3,0.04290130001027137
|
||||||
|
HashTable,shuffled,вставка,4,0.04275970003800467
|
||||||
|
HashTable,shuffled,вставка,5,0.04289869999047369
|
||||||
|
HashTable,shuffled,поиск,1,0.00041800003964453936
|
||||||
|
HashTable,shuffled,поиск,2,0.00037750002229586244
|
||||||
|
HashTable,shuffled,поиск,3,0.0004216000088490546
|
||||||
|
HashTable,shuffled,поиск,4,0.00037650001468136907
|
||||||
|
HashTable,shuffled,поиск,5,0.00037869997322559357
|
||||||
|
HashTable,shuffled,удаление,1,0.00024719996144995093
|
||||||
|
HashTable,shuffled,удаление,2,0.0002562999725341797
|
||||||
|
HashTable,shuffled,удаление,3,0.00026979995891451836
|
||||||
|
HashTable,shuffled,удаление,4,0.00027629995020106435
|
||||||
|
HashTable,shuffled,удаление,5,0.000278000021353364
|
||||||
|
HashTable,sorted,вставка,1,0.044519999995827675
|
||||||
|
HashTable,sorted,вставка,2,0.043910799955483526
|
||||||
|
HashTable,sorted,вставка,3,0.04366250004386529
|
||||||
|
HashTable,sorted,вставка,4,0.04391039995243773
|
||||||
|
HashTable,sorted,вставка,5,0.04331600002478808
|
||||||
|
HashTable,sorted,поиск,1,0.0003066000062972307
|
||||||
|
HashTable,sorted,поиск,2,0.00029749999521300197
|
||||||
|
HashTable,sorted,поиск,3,0.00030989997321739793
|
||||||
|
HashTable,sorted,поиск,4,0.0003060000017285347
|
||||||
|
HashTable,sorted,поиск,5,0.0003185000387020409
|
||||||
|
HashTable,sorted,удаление,1,0.00017769995611160994
|
||||||
|
HashTable,sorted,удаление,2,0.00021810003090649843
|
||||||
|
HashTable,sorted,удаление,3,0.0002011999604292214
|
||||||
|
HashTable,sorted,удаление,4,0.00024099997244775295
|
||||||
|
HashTable,sorted,удаление,5,0.00023500004317611456
|
||||||
|
BST,shuffled,вставка,1,0.023512399988248944
|
||||||
|
BST,shuffled,вставка,2,0.023390999995172024
|
||||||
|
BST,shuffled,вставка,3,0.02383040002314374
|
||||||
|
BST,shuffled,вставка,4,0.02347449999069795
|
||||||
|
BST,shuffled,вставка,5,0.023390699992887676
|
||||||
|
BST,shuffled,поиск,1,0.0002652000403031707
|
||||||
|
BST,shuffled,поиск,2,0.00026300002355128527
|
||||||
|
BST,shuffled,поиск,3,0.0002535999519750476
|
||||||
|
BST,shuffled,поиск,4,0.0002691000117920339
|
||||||
|
BST,shuffled,поиск,5,0.000271800032351166
|
||||||
|
BST,shuffled,удаление,1,0.00015969999367371202
|
||||||
|
BST,shuffled,удаление,2,0.00016689999029040337
|
||||||
|
BST,shuffled,удаление,3,0.00015079998411238194
|
||||||
|
BST,shuffled,удаление,4,0.000139000010676682
|
||||||
|
BST,shuffled,удаление,5,0.00014590000500902534
|
||||||
|
BST,sorted,вставка,1,1.4365359999937937
|
||||||
|
BST,sorted,вставка,2,1.4347687999834307
|
||||||
|
BST,sorted,вставка,3,1.4342009999672882
|
||||||
|
BST,sorted,вставка,4,1.4454721999936737
|
||||||
|
BST,sorted,вставка,5,1.4339254000224173
|
||||||
|
BST,sorted,поиск,1,0.0064765000133775175
|
||||||
|
BST,sorted,поиск,2,0.006033400015439838
|
||||||
|
BST,sorted,поиск,3,0.005681200011167675
|
||||||
|
BST,sorted,поиск,4,0.005705999967176467
|
||||||
|
BST,sorted,поиск,5,0.006056099955458194
|
||||||
|
BST,sorted,удаление,1,0.00313799997093156
|
||||||
|
BST,sorted,удаление,2,0.002808899967931211
|
||||||
|
BST,sorted,удаление,3,0.0027692000148817897
|
||||||
|
BST,sorted,удаление,4,0.001900400035083294
|
||||||
|
BST,sorted,удаление,5,0.0019530000281520188
|
||||||
|
366
starikovta/phonebook.py
Normal file
|
|
@ -0,0 +1,366 @@
|
||||||
|
import time
|
||||||
|
import random
|
||||||
|
import csv
|
||||||
|
import sys
|
||||||
|
sys.setrecursionlimit (50000)
|
||||||
|
from datetime import datetime
|
||||||
|
|
||||||
|
# ==================== СВЯЗНЫЙ СПИСОК ====================
|
||||||
|
|
||||||
|
def ll_insert(head, name, phone):
|
||||||
|
"""Добавляет или обновляет запись в связном списке"""
|
||||||
|
# Проверяем, не существует ли уже такой name
|
||||||
|
curr = head
|
||||||
|
while curr:
|
||||||
|
if curr['name'] == name:
|
||||||
|
curr['phone'] = phone # обновляем
|
||||||
|
return head
|
||||||
|
curr = curr['next']
|
||||||
|
|
||||||
|
# Если не нашли, вставляем в конец
|
||||||
|
new_node = {'name': name, 'phone': phone, 'next': None}
|
||||||
|
|
||||||
|
if head is None:
|
||||||
|
return new_node
|
||||||
|
|
||||||
|
curr = head
|
||||||
|
while curr['next']:
|
||||||
|
curr = curr['next']
|
||||||
|
curr['next'] = new_node
|
||||||
|
return head
|
||||||
|
|
||||||
|
def ll_find(head, name):
|
||||||
|
"""Ищет запись по имени, возвращает телефон или None"""
|
||||||
|
curr = head
|
||||||
|
while curr:
|
||||||
|
if curr['name'] == name:
|
||||||
|
return curr['phone']
|
||||||
|
curr = curr['next']
|
||||||
|
return None
|
||||||
|
|
||||||
|
def ll_delete(head, name):
|
||||||
|
"""Удаляет запись по имени, возвращает новую голову"""
|
||||||
|
if head is None:
|
||||||
|
return None
|
||||||
|
|
||||||
|
# Если удаляем голову
|
||||||
|
if head['name'] == name:
|
||||||
|
return head['next']
|
||||||
|
|
||||||
|
# Ищем элемент перед удаляемым
|
||||||
|
curr = head
|
||||||
|
while curr['next']:
|
||||||
|
if curr['next']['name'] == name:
|
||||||
|
curr['next'] = curr['next']['next']
|
||||||
|
return head
|
||||||
|
curr = curr['next']
|
||||||
|
return head
|
||||||
|
|
||||||
|
def ll_list_all(head):
|
||||||
|
"""Собирает все записи и сортирует по имени"""
|
||||||
|
records = []
|
||||||
|
curr = head
|
||||||
|
while curr:
|
||||||
|
records.append((curr['name'], curr['phone']))
|
||||||
|
curr = curr['next']
|
||||||
|
# Сортируем по имени
|
||||||
|
records.sort(key=lambda x: x[0])
|
||||||
|
return records
|
||||||
|
|
||||||
|
# ==================== ХЕШ-ТАБЛИЦА ====================
|
||||||
|
|
||||||
|
def hash_function(name, size):
|
||||||
|
"""Простая хеш-функция"""
|
||||||
|
return sum(ord(c) for c in name) % size
|
||||||
|
|
||||||
|
def ht_insert(buckets, name, phone):
|
||||||
|
"""Вставляет запись в хеш-таблицу"""
|
||||||
|
index = hash_function(name, len(buckets))
|
||||||
|
# Используем ll_insert для бакета
|
||||||
|
buckets[index] = ll_insert(buckets[index], name, phone)
|
||||||
|
return buckets
|
||||||
|
|
||||||
|
def ht_find(buckets, name):
|
||||||
|
"""Ищет запись в хеш-таблице"""
|
||||||
|
index = hash_function(name, len(buckets))
|
||||||
|
return ll_find(buckets[index], name)
|
||||||
|
|
||||||
|
def ht_delete(buckets, name):
|
||||||
|
"""Удаляет запись из хеш-таблицы"""
|
||||||
|
index = hash_function(name, len(buckets))
|
||||||
|
buckets[index] = ll_delete(buckets[index], name)
|
||||||
|
return buckets
|
||||||
|
|
||||||
|
def ht_list_all(buckets):
|
||||||
|
"""Собирает все записи из всех бакетов и сортирует"""
|
||||||
|
all_records = []
|
||||||
|
for bucket in buckets:
|
||||||
|
curr = bucket
|
||||||
|
while curr:
|
||||||
|
all_records.append((curr['name'], curr['phone']))
|
||||||
|
curr = curr['next']
|
||||||
|
all_records.sort(key=lambda x: x[0])
|
||||||
|
return all_records
|
||||||
|
|
||||||
|
# ==================== БИНАРНОЕ ДЕРЕВО ПОИСКА ====================
|
||||||
|
|
||||||
|
def bst_insert(root, name, phone):
|
||||||
|
"""Вставляет запись в BST (рекурсивно)"""
|
||||||
|
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:
|
||||||
|
# Обновляем существующую запись
|
||||||
|
root['phone'] = phone
|
||||||
|
return root
|
||||||
|
|
||||||
|
def bst_find(root, name):
|
||||||
|
"""Ищет запись в BST"""
|
||||||
|
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_find_min(node):
|
||||||
|
"""Находит узел с минимальным значением"""
|
||||||
|
current = node
|
||||||
|
while current and current['left']:
|
||||||
|
current = current['left']
|
||||||
|
return current
|
||||||
|
|
||||||
|
def bst_delete(root, name):
|
||||||
|
"""Удаляет запись из BST"""
|
||||||
|
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:
|
||||||
|
# Узел найден
|
||||||
|
if root['left'] is None:
|
||||||
|
return root['right']
|
||||||
|
elif root['right'] is None:
|
||||||
|
return root['left']
|
||||||
|
|
||||||
|
# Узел с двумя детьми
|
||||||
|
temp = bst_find_min(root['right'])
|
||||||
|
root['name'] = temp['name']
|
||||||
|
root['phone'] = temp['phone']
|
||||||
|
root['right'] = bst_delete(root['right'], temp['name'])
|
||||||
|
return root
|
||||||
|
|
||||||
|
def bst_list_all(root):
|
||||||
|
"""Центрированный обход (возвращает отсортированный список)"""
|
||||||
|
records = []
|
||||||
|
|
||||||
|
def inorder_traversal(node):
|
||||||
|
if node:
|
||||||
|
inorder_traversal(node['left'])
|
||||||
|
records.append((node['name'], node['phone']))
|
||||||
|
inorder_traversal(node['right'])
|
||||||
|
|
||||||
|
inorder_traversal(root)
|
||||||
|
return records
|
||||||
|
|
||||||
|
# ==================== ГЕНЕРАЦИЯ ТЕСТОВЫХ ДАННЫХ ====================
|
||||||
|
|
||||||
|
def generate_test_data(n=10000):
|
||||||
|
"""Генерирует shuffled и sorted версии данных"""
|
||||||
|
# Генерируем имена с небольшим количеством коллизий
|
||||||
|
names_pool = [f"User_{i:05d}" for i in range(n // 10)] # 1000 уникальных имен
|
||||||
|
records = []
|
||||||
|
|
||||||
|
for i in range(n):
|
||||||
|
name = random.choice(names_pool) # повторяющиеся имена для коллизий
|
||||||
|
phone = f"+7-999-{random.randint(1000000, 9999999)}"
|
||||||
|
records.append((name, phone))
|
||||||
|
|
||||||
|
# Создаем shuffled и sorted версии
|
||||||
|
records_shuffled = records.copy()
|
||||||
|
random.shuffle(records_shuffled)
|
||||||
|
|
||||||
|
records_sorted = sorted(records, key=lambda x: x[0])
|
||||||
|
|
||||||
|
return records_shuffled, records_sorted
|
||||||
|
|
||||||
|
# ==================== ЗАМЕРЫ ВРЕМЕНИ ====================
|
||||||
|
|
||||||
|
def measure_insertion(struct_type, records, buckets_size=None):
|
||||||
|
"""Замеряет время вставки всех записей"""
|
||||||
|
if struct_type == "LinkedList":
|
||||||
|
head = None
|
||||||
|
start = time.perf_counter()
|
||||||
|
for name, phone in records:
|
||||||
|
head = ll_insert(head, name, phone)
|
||||||
|
end = time.perf_counter()
|
||||||
|
elif struct_type == "HashTable":
|
||||||
|
if buckets_size is None:
|
||||||
|
buckets_size = 1000
|
||||||
|
buckets = [None] * buckets_size
|
||||||
|
start = time.perf_counter()
|
||||||
|
for name, phone in records:
|
||||||
|
buckets = ht_insert(buckets, name, phone)
|
||||||
|
end = time.perf_counter()
|
||||||
|
elif struct_type == "BST":
|
||||||
|
root = None
|
||||||
|
start = time.perf_counter()
|
||||||
|
for name, phone in records:
|
||||||
|
root = bst_insert(root, name, phone)
|
||||||
|
end = time.perf_counter()
|
||||||
|
else:
|
||||||
|
return None, None
|
||||||
|
|
||||||
|
elapsed = end - start
|
||||||
|
return elapsed, (head if struct_type == "LinkedList" else (buckets if struct_type == "HashTable" else root))
|
||||||
|
|
||||||
|
def measure_find(struct_type, data_structure, records, num_existing=100, num_nonexistent=10):
|
||||||
|
"""Замеряет время поиска записей"""
|
||||||
|
# Выбираем существующие записи
|
||||||
|
existing_names = random.sample([name for name, _ in records[:len(records)//2]], min(num_existing, len(records)))
|
||||||
|
|
||||||
|
# Создаем несуществующие имена
|
||||||
|
nonexistent_names = [f"None_{i}" for i in range(num_nonexistent)]
|
||||||
|
|
||||||
|
all_queries = existing_names + nonexistent_names
|
||||||
|
random.shuffle(all_queries)
|
||||||
|
|
||||||
|
start = time.perf_counter()
|
||||||
|
for name in all_queries:
|
||||||
|
if struct_type == "LinkedList":
|
||||||
|
ll_find(data_structure, name)
|
||||||
|
elif struct_type == "HashTable":
|
||||||
|
ht_find(data_structure, name)
|
||||||
|
elif struct_type == "BST":
|
||||||
|
bst_find(data_structure, name)
|
||||||
|
end = time.perf_counter()
|
||||||
|
|
||||||
|
return end - start
|
||||||
|
|
||||||
|
def measure_delete(struct_type, data_structure, records, num_to_delete=50):
|
||||||
|
"""Замеряет время удаления записей"""
|
||||||
|
# Выбираем случайные имена для удаления
|
||||||
|
names_to_delete = random.sample([name for name, _ in records[:len(records)//2]], min(num_to_delete, len(records)))
|
||||||
|
|
||||||
|
start = time.perf_counter()
|
||||||
|
for name in names_to_delete:
|
||||||
|
if struct_type == "LinkedList":
|
||||||
|
data_structure = ll_delete(data_structure, name)
|
||||||
|
elif struct_type == "HashTable":
|
||||||
|
data_structure = ht_delete(data_structure, name)
|
||||||
|
elif struct_type == "BST":
|
||||||
|
data_structure = bst_delete(data_structure, name)
|
||||||
|
end = time.perf_counter()
|
||||||
|
|
||||||
|
return end - start
|
||||||
|
|
||||||
|
# ==================== ОСНОВНОЙ ЭКСПЕРИМЕНТ ====================
|
||||||
|
|
||||||
|
def run_experiment():
|
||||||
|
"""Запускает все эксперименты и сохраняет результаты"""
|
||||||
|
|
||||||
|
print("Генерация тестовых данных...")
|
||||||
|
records_shuffled, records_sorted = generate_test_data(10000)
|
||||||
|
|
||||||
|
structures = ["LinkedList", "HashTable", "BST"]
|
||||||
|
modes = {"shuffled": records_shuffled, "sorted": records_sorted}
|
||||||
|
|
||||||
|
all_results = []
|
||||||
|
all_results.append(["Структура", "Режим", "Операция", "Повторение", "Время (сек)"])
|
||||||
|
|
||||||
|
# Количество повторений
|
||||||
|
repeats = 5
|
||||||
|
|
||||||
|
for struct in structures:
|
||||||
|
for mode_name, records in modes.items():
|
||||||
|
print(f"\nТестирование: {struct}, режим {mode_name}")
|
||||||
|
|
||||||
|
# Вставка
|
||||||
|
insertion_times = []
|
||||||
|
for rep in range(repeats):
|
||||||
|
print(f" Вставка, повторение {rep+1}/{repeats}...")
|
||||||
|
elapsed, data_struct = measure_insertion(struct, records)
|
||||||
|
insertion_times.append(elapsed)
|
||||||
|
all_results.append([struct, mode_name, "вставка", rep+1, elapsed])
|
||||||
|
|
||||||
|
# Используем последнюю структуру для поиска и удаления
|
||||||
|
# (пересоздаем для чистоты эксперимента)
|
||||||
|
_, data_struct = measure_insertion(struct, records)
|
||||||
|
|
||||||
|
# Поиск
|
||||||
|
find_times = []
|
||||||
|
for rep in range(repeats):
|
||||||
|
print(f" Поиск, повторение {rep+1}/{repeats}...")
|
||||||
|
elapsed = measure_find(struct, data_struct, records)
|
||||||
|
find_times.append(elapsed)
|
||||||
|
all_results.append([struct, mode_name, "поиск", rep+1, elapsed])
|
||||||
|
|
||||||
|
# Удаление
|
||||||
|
delete_times = []
|
||||||
|
# Создаем свежую структуру для удаления
|
||||||
|
_, fresh_data_struct = measure_insertion(struct, records)
|
||||||
|
for rep in range(repeats):
|
||||||
|
print(f" Удаление, повторение {rep+1}/{repeats}...")
|
||||||
|
elapsed = measure_delete(struct, fresh_data_struct, records)
|
||||||
|
delete_times.append(elapsed)
|
||||||
|
all_results.append([struct, mode_name, "удаление", rep+1, elapsed])
|
||||||
|
|
||||||
|
# Выводим средние значения
|
||||||
|
print(f" Среднее время вставки: {sum(insertion_times)/len(insertion_times):.6f} сек")
|
||||||
|
print(f" Среднее время поиска: {sum(find_times)/len(find_times):.6f} сек")
|
||||||
|
print(f" Среднее время удаления: {sum(delete_times)/len(delete_times):.6f} сек")
|
||||||
|
|
||||||
|
# Сохраняем результаты в CSV
|
||||||
|
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||||
|
csv_filename = f"experiment_results_{timestamp}.csv"
|
||||||
|
|
||||||
|
with open(csv_filename, 'w', newline='', encoding='utf-8') as f:
|
||||||
|
writer = csv.writer(f)
|
||||||
|
writer.writerows(all_results)
|
||||||
|
|
||||||
|
print(f"\nРезультаты сохранены в файл: {csv_filename}")
|
||||||
|
|
||||||
|
# Сохраняем также средние значения для удобства
|
||||||
|
avg_results = []
|
||||||
|
avg_results.append(["Структура", "Режим", "Операция", "Среднее время (сек)", "Мин", "Макс"])
|
||||||
|
|
||||||
|
# Группируем по структуре, режиму, операции
|
||||||
|
grouped = {}
|
||||||
|
for row in all_results[1:]: # пропускаем заголовок
|
||||||
|
struct, mode, op, rep, time_val = row
|
||||||
|
key = (struct, mode, op)
|
||||||
|
if key not in grouped:
|
||||||
|
grouped[key] = []
|
||||||
|
grouped[key].append(time_val)
|
||||||
|
|
||||||
|
for (struct, mode, op), times in grouped.items():
|
||||||
|
avg_time = sum(times) / len(times)
|
||||||
|
min_time = min(times)
|
||||||
|
max_time = max(times)
|
||||||
|
avg_results.append([struct, mode, op, avg_time, min_time, max_time])
|
||||||
|
|
||||||
|
avg_filename = f"average_results_{timestamp}.csv"
|
||||||
|
with open(avg_filename, 'w', newline='', encoding='utf-8') as f:
|
||||||
|
writer = csv.writer(f)
|
||||||
|
writer.writerows(avg_results)
|
||||||
|
|
||||||
|
print(f"Средние значения сохранены в файл: {avg_filename}")
|
||||||
|
|
||||||
|
return all_results, avg_results
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
print("Начало эксперимента...")
|
||||||
|
print("="*50)
|
||||||
|
results, avg_results = run_experiment()
|
||||||
|
print("="*50)
|
||||||
|
print("Эксперимент завершен!")
|
||||||