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develop
...
SmirnovaVY
5
.idea/.gitignore
vendored
5
.idea/.gitignore
vendored
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@ -1,5 +0,0 @@
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# Игнорируемые файлы по умолчанию
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/shelf/
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/workspace.xml
|
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# HTTP-клиент на основе редактора
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/httpRequests/
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@ -1,8 +0,0 @@
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<?xml version="1.0" encoding="UTF-8"?>
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||||
<module type="PYTHON_MODULE" version="4">
|
||||
<component name="NewModuleRootManager">
|
||||
<content url="file://$MODULE_DIR$" />
|
||||
<orderEntry type="jdk" jdkName="Python 3.14" jdkType="Python SDK" />
|
||||
<orderEntry type="sourceFolder" forTests="false" />
|
||||
</component>
|
||||
</module>
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||||
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@ -1,6 +0,0 @@
|
|||
<component name="InspectionProjectProfileManager">
|
||||
<settings>
|
||||
<option name="USE_PROJECT_PROFILE" value="false" />
|
||||
<version value="1.0" />
|
||||
</settings>
|
||||
</component>
|
||||
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@ -1,7 +0,0 @@
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|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
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||||
<component name="Black">
|
||||
<option name="sdkName" value="Python 3.14" />
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||||
</component>
|
||||
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.14" project-jdk-type="Python SDK" />
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||||
</project>
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||||
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@ -1,8 +0,0 @@
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|||
<?xml version="1.0" encoding="UTF-8"?>
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||||
<project version="4">
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||||
<component name="ProjectModuleManager">
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||||
<modules>
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||||
<module fileurl="file://$PROJECT_DIR$/.idea/2026-rff_mp.iml" filepath="$PROJECT_DIR$/.idea/2026-rff_mp.iml" />
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</modules>
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||||
</component>
|
||||
</project>
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||||
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@ -1,6 +0,0 @@
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|||
<?xml version="1.0" encoding="UTF-8"?>
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||||
<project version="4">
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||||
<component name="VcsDirectoryMappings">
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||||
<mapping directory="" vcs="Git" />
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||||
</component>
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||||
</project>
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@ -1 +0,0 @@
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428b
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@ -1,31 +0,0 @@
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Structure,Mode,Repetition,Insert (sec),Find (sec),Delete (sec)
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LinkedList,random,1,0.022518936000324175,0.0022566010002265102,0.00023215900000650436
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LinkedList,random,2,0.020449046000067028,0.00233427400007713,0.0002826350000759703
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LinkedList,random,3,0.020126345999869955,0.002262161000089691,0.0002053490002253966
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LinkedList,random,4,0.018700520000038523,0.0021239550001155294,0.00021164700001463643
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LinkedList,random,5,0.019754801000090083,0.0024997460000122373,0.00023158399972089683
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HashTable,random,1,0.0029892609995840758,0.0003534970001055626,2.990000029967632e-05
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HashTable,random,2,0.00424448100011432,0.00041066700032388326,4.1896999846358085e-05
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HashTable,random,3,0.004175077000127203,0.0004925200000798213,2.9787000130454544e-05
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HashTable,random,4,0.004567926000163425,0.00033349500017720857,3.164999998261919e-05
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HashTable,random,5,0.0026621540000633104,0.00031125700024858816,2.81510001514107e-05
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BST,random,1,0.0011096680000264314,9.346200022264384e-05,3.9635000121052144e-05
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BST,random,2,0.0010248069997942366,9.059800004251883e-05,2.1142000150575768e-05
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BST,random,3,0.0010313749999113497,9.237799986294704e-05,1.8248000287712784e-05
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BST,random,4,0.0010483440000825794,9.526299982098863e-05,0.0001046150000547641
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BST,random,5,0.0010863010002140072,8.332400011568097e-05,1.7150000076071592e-05
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LinkedList,sorted,1,0.022635587000422674,0.0023248429997693165,0.00031860600029176567
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LinkedList,sorted,2,0.02307340400011526,0.002558939999744325,0.00023637899994355394
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LinkedList,sorted,3,0.01936496400003307,0.002565375999893149,0.00019060200020248885
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LinkedList,sorted,4,0.018800279000060982,0.0021075829999972484,0.00018179399967266363
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LinkedList,sorted,5,0.019234453000080975,0.002213534000020445,0.0002037049998762086
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HashTable,sorted,1,0.0031771270000717777,0.0006652990000475256,6.005399973219028e-05
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HashTable,sorted,2,0.004056166999816924,0.00058001300021715,3.078500003539375e-05
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HashTable,sorted,3,0.00331192200019359,0.00027228699991610483,2.684700029931264e-05
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HashTable,sorted,4,0.002749069000401505,0.0002677190000213159,2.1935999939159956e-05
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HashTable,sorted,5,0.002638604000367195,0.0003338189999340102,1.83020001713885e-05
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BST,sorted,1,0.037994623000031424,0.0035877690002052987,0.0011276019999968412
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BST,sorted,2,0.038043681000090146,0.0031297909999921103,0.00094645799981663
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BST,sorted,3,0.03629641699990316,0.0027566620001380215,0.0012528499996733444
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BST,sorted,4,0.03509285000018281,0.003267435999987356,0.0011822649998975976
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BST,sorted,5,0.038755655999921146,0.0064144259999920905,0.0018493429997761268
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Binary file not shown.
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Before Width: | Height: | Size: 79 KiB |
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@ -1,335 +0,0 @@
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import random
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import time
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import sys
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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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import numpy as np
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sys.setrecursionlimit(10000)
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ll_head = None
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def ll_insert(name, phone):
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global ll_head
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cur = ll_head
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while cur is not None:
|
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if cur['name'] == name:
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cur['phone'] = phone
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return
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cur = cur['next']
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new_node = {'name': name, 'phone': phone, 'next': ll_head}
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ll_head = new_node
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|
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def ll_find(name):
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cur = ll_head
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while cur is not None:
|
||||
if cur['name'] == name:
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return cur['phone']
|
||||
cur = cur['next']
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return None
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||||
|
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def ll_delete(name):
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global ll_head
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if ll_head is None:
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||||
return
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||||
if ll_head['name'] == name:
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ll_head = ll_head['next']
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return
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prev = ll_head
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||||
cur = ll_head['next']
|
||||
while cur is not None:
|
||||
if cur['name'] == name:
|
||||
prev['next'] = cur['next']
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return
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prev = cur
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||||
cur = cur['next']
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||||
|
||||
def ll_list_all():
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||||
records = []
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cur = ll_head
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||||
while cur is not None:
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records.append((cur['name'], cur['phone']))
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||||
cur = cur['next']
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||||
records.sort(key=lambda x: x[0])
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||||
return records
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||||
|
||||
BUCKET_COUNT = 10
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||||
buckets = [None] * BUCKET_COUNT
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||||
|
||||
def hash_func(name):
|
||||
s = 0
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for ch in name:
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s += ord(ch)
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return s % BUCKET_COUNT
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||||
|
||||
def ht_insert(name, phone):
|
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global buckets
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idx = hash_func(name)
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cur = buckets[idx]
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while cur is not None:
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||||
if cur['name'] == name:
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cur['phone'] = phone
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return
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cur = cur['next']
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new_node = {'name': name, 'phone': phone, 'next': buckets[idx]}
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buckets[idx] = new_node
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|
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def ht_find(name):
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idx = hash_func(name)
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cur = buckets[idx]
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while cur is not None:
|
||||
if cur['name'] == name:
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return cur['phone']
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cur = cur['next']
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return None
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def ht_delete(name):
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global buckets
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idx = hash_func(name)
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head = buckets[idx]
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if head is None:
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return
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if head['name'] == name:
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buckets[idx] = head['next']
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return
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prev = head
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cur = head['next']
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while cur is not None:
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||||
if cur['name'] == name:
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prev['next'] = cur['next']
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return
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prev = cur
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cur = cur['next']
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def ht_list_all():
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all_records = []
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for head in buckets:
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cur = head
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while cur is not None:
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all_records.append((cur['name'], cur['phone']))
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cur = cur['next']
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all_records.sort(key=lambda x: x[0])
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return all_records
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bst_root = None
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||||
def bst_create_node(name, phone):
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return {'name': name, 'phone': phone, 'left': None, 'right': None}
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def bst_insert(name, phone):
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global bst_root
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if bst_root is None:
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bst_root = bst_create_node(name, phone)
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return
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current = bst_root
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while True:
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if name == current['name']:
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current['phone'] = phone
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return
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||||
elif name < current['name']:
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if current['left'] is None:
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current['left'] = bst_create_node(name, phone)
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return
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||||
current = current['left']
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||||
else:
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||||
if current['right'] is None:
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current['right'] = bst_create_node(name, phone)
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||||
return
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||||
current = current['right']
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||||
|
||||
def bst_find(name):
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||||
current = bst_root
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while current is not None:
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if name == current['name']:
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return current['phone']
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elif name < current['name']:
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current = current['left']
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else:
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current = current['right']
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return None
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|
||||
def find_min(node):
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while node['left'] is not None:
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node = node['left']
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return node
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|
||||
def bst_delete(name):
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global bst_root
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def delete_rec(node):
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if node is None:
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return None
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if name < node['name']:
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node['left'] = delete_rec(node['left'])
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||||
elif name > node['name']:
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||||
node['right'] = delete_rec(node['right'])
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||||
else:
|
||||
if node['left'] is None:
|
||||
return node['right']
|
||||
if node['right'] is None:
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||||
return node['left']
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min_node = find_min(node['right'])
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node['name'] = min_node['name']
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node['phone'] = min_node['phone']
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node['right'] = delete_rec(node['right'])
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return node
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||||
bst_root = delete_rec(bst_root)
|
||||
|
||||
def bst_list_all():
|
||||
result = []
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||||
def inorder(node):
|
||||
if node is None:
|
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return
|
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inorder(node['left'])
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result.append((node['name'], node['phone']))
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inorder(node['right'])
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inorder(bst_root)
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return result
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|
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def generate_records(n):
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records = []
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for i in range(1, n+1):
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name = f"User_{i:05d}"
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phone = f"{random.randint(100,999)}-{random.randint(1000,9999)}"
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records.append((name, phone))
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return records
|
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|
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def run_experiment():
|
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N = 1000
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base = generate_records(N)
|
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shuffled = base.copy()
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random.shuffle(shuffled)
|
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sorted_records = sorted(base, key=lambda x: x[0])
|
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|
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structures = [
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('LinkedList', ll_insert, ll_find, ll_delete, ll_list_all),
|
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('HashTable', ht_insert, ht_find, ht_delete, ht_list_all),
|
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('BST', bst_insert, bst_find, bst_delete, bst_list_all)
|
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]
|
||||
|
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all_results = [] # для CSV: список словарей
|
||||
repeats = 5
|
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|
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for mode_name, data in [('random', shuffled), ('sorted', sorted_records)]:
|
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for struct_name, ins, fnd, dele, lst in structures:
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print(f"Testing {struct_name} on {mode_name}...")
|
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for rep in range(repeats):
|
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# сброс структур
|
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global ll_head, buckets, bst_root
|
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ll_head = None
|
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buckets = [None] * BUCKET_COUNT
|
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bst_root = None
|
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|
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# вставка
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||||
t0 = time.perf_counter()
|
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for name, phone in data:
|
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ins(name, phone)
|
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t1 = time.perf_counter()
|
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insert_time = t1 - t0
|
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|
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# поиск 110 записей (100 существующих + 10 несуществующих)
|
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existing = [name for name, _ in data]
|
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sample = random.sample(existing, 100)
|
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none_names = [f"None_{i}" for i in range(10)]
|
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search_names = sample + none_names
|
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random.shuffle(search_names)
|
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t0 = time.perf_counter()
|
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for name in search_names:
|
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fnd(name)
|
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t1 = time.perf_counter()
|
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find_time = t1 - t0
|
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|
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# удаление 10 записей
|
||||
to_delete = random.sample(existing, 10)
|
||||
t0 = time.perf_counter()
|
||||
for name in to_delete:
|
||||
dele(name)
|
||||
t1 = time.perf_counter()
|
||||
delete_time = t1 - t0
|
||||
|
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all_results.append({
|
||||
'Structure': struct_name,
|
||||
'Mode': mode_name,
|
||||
'Repetition': rep+1,
|
||||
'Insert (sec)': insert_time,
|
||||
'Find (sec)': find_time,
|
||||
'Delete (sec)': delete_time
|
||||
})
|
||||
|
||||
# Сохранение CSV
|
||||
output_dir = "docs/data/1-st"
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
csv_path = os.path.join(output_dir, "experiment_results.csv")
|
||||
with open(csv_path, 'w', newline='', encoding='utf-8') as f:
|
||||
fieldnames = ['Structure', 'Mode', 'Repetition', 'Insert (sec)', 'Find (sec)', 'Delete (sec)']
|
||||
writer = csv.DictWriter(f, fieldnames=fieldnames)
|
||||
writer.writeheader()
|
||||
writer.writerows(all_results)
|
||||
print(f"\nРезультаты сохранены в {csv_path}")
|
||||
|
||||
avg_data = {}
|
||||
for r in all_results:
|
||||
key = (r['Structure'], r['Mode'])
|
||||
if key not in avg_data:
|
||||
avg_data[key] = {'Insert': [], 'Find': [], 'Delete': []}
|
||||
avg_data[key]['Insert'].append(r['Insert (sec)'])
|
||||
avg_data[key]['Find'].append(r['Find (sec)'])
|
||||
avg_data[key]['Delete'].append(r['Delete (sec)'])
|
||||
|
||||
structures_list = ['LinkedList', 'HashTable', 'BST']
|
||||
modes_list = ['random', 'sorted']
|
||||
insert_vals = {mode: [] for mode in modes_list}
|
||||
find_vals = {mode: [] for mode in modes_list}
|
||||
delete_vals = {mode: [] for mode in modes_list}
|
||||
|
||||
for mode in modes_list:
|
||||
for struct in structures_list:
|
||||
key = (struct, mode)
|
||||
if key in avg_data:
|
||||
insert_avg = sum(avg_data[key]['Insert']) / len(avg_data[key]['Insert'])
|
||||
find_avg = sum(avg_data[key]['Find']) / len(avg_data[key]['Find'])
|
||||
delete_avg = sum(avg_data[key]['Delete']) / len(avg_data[key]['Delete'])
|
||||
else:
|
||||
insert_avg = find_avg = delete_avg = 0
|
||||
insert_vals[mode].append(insert_avg)
|
||||
find_vals[mode].append(find_avg)
|
||||
delete_vals[mode].append(delete_avg)
|
||||
|
||||
# Рисуем три столбчатые диаграммы
|
||||
fig, axes = plt.subplots(1, 3, figsize=(15, 5))
|
||||
x = np.arange(len(structures_list))
|
||||
width = 0.35
|
||||
|
||||
for ax, op_data, op_label, ylabel in zip(
|
||||
axes,
|
||||
[insert_vals, find_vals, delete_vals],
|
||||
['Insert', 'Find', 'Delete'],
|
||||
['Время вставки (с)', 'Время поиска (с)', 'Время удаления (с)']
|
||||
):
|
||||
random_vals = op_data['random']
|
||||
sorted_vals = op_data['sorted']
|
||||
ax.bar(x - width/2, random_vals, width, label='Случайный порядок', color='skyblue')
|
||||
ax.bar(x + width/2, sorted_vals, width, label='Отсортированный порядок', color='salmon')
|
||||
ax.set_xticks(x)
|
||||
ax.set_xticklabels(structures_list)
|
||||
ax.set_ylabel(ylabel)
|
||||
ax.set_title(op_label)
|
||||
ax.legend()
|
||||
|
||||
plt.tight_layout()
|
||||
png_path = os.path.join(output_dir, "performance_comparison.png")
|
||||
plt.savefig(png_path, dpi=150)
|
||||
print(f"График сохранён в {png_path}")
|
||||
plt.show()
|
||||
|
||||
# Вывод средних значений в консоль (для отчёта)
|
||||
print("\nСредние значения (сек):")
|
||||
print("Структура\tРежим\tВставка\tПоиск\tУдаление")
|
||||
for (struct, mode), vals in avg_data.items():
|
||||
ins_avg = sum(vals['Insert'])/len(vals['Insert'])
|
||||
find_avg = sum(vals['Find'])/len(vals['Find'])
|
||||
del_avg = sum(vals['Delete'])/len(vals['Delete'])
|
||||
print(f"{struct}\t{mode}\t{ins_avg:.6f}\t{find_avg:.6f}\t{del_avg:.6f}")
|
||||
|
||||
if __name__ == '__main__':
|
||||
run_experiment()
|
||||
|
|
@ -1,430 +0,0 @@
|
|||
import time
|
||||
import random
|
||||
import csv
|
||||
import os
|
||||
from collections import deque
|
||||
import heapq
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
|
||||
class Cell:
|
||||
def __init__(self, x, y, is_wall=False, is_start=False, is_exit=False):
|
||||
self.x = x
|
||||
self.y = y
|
||||
self.is_wall = is_wall
|
||||
self.is_start = is_start
|
||||
self.is_exit = is_exit
|
||||
|
||||
def is_passable(self):
|
||||
return not self.is_wall
|
||||
|
||||
|
||||
class Maze:
|
||||
def __init__(self, width, height):
|
||||
self.width = width
|
||||
self.height = height
|
||||
self.grid = [[Cell(x, y) for y in range(height)] for x in range(width)]
|
||||
self.start_cell = None
|
||||
self.exit_cell = None
|
||||
|
||||
def get_cell(self, x, y):
|
||||
if 0 <= x < self.width and 0 <= y < self.height:
|
||||
return self.grid[x][y]
|
||||
return None
|
||||
|
||||
def get_neighbors(self, cell):
|
||||
neighbors = []
|
||||
for dx, dy in [(-1,0), (1,0), (0,-1), (0,1)]:
|
||||
nx, ny = cell.x + dx, cell.y + dy
|
||||
neighbor = self.get_cell(nx, ny)
|
||||
if neighbor and neighbor.is_passable():
|
||||
neighbors.append(neighbor)
|
||||
return neighbors
|
||||
|
||||
def save_to_file(self, filename):
|
||||
"""Сохраняет лабиринт в текстовый файл."""
|
||||
with open(filename, 'w', encoding='utf-8') as f:
|
||||
for y in range(self.height):
|
||||
row = ''
|
||||
for x in range(self.width):
|
||||
cell = self.get_cell(x, y)
|
||||
if cell.is_wall:
|
||||
row += '#'
|
||||
elif cell.is_start:
|
||||
row += 'S'
|
||||
elif cell.is_exit:
|
||||
row += 'E'
|
||||
else:
|
||||
row += ' '
|
||||
f.write(row + '\n')
|
||||
|
||||
|
||||
|
||||
class MazeBuilder:
|
||||
def build_from_file(self, filename):
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
class TextFileMazeBuilder(MazeBuilder):
|
||||
def build_from_file(self, filename):
|
||||
with open(filename, 'r', encoding='utf-8') as f:
|
||||
lines = f.readlines()
|
||||
lines = [line.rstrip('\n') for line in lines if line.strip() != '']
|
||||
if not lines:
|
||||
raise ValueError("Файл пуст")
|
||||
height = len(lines)
|
||||
width = max(len(line) for line in lines)
|
||||
maze = Maze(width, height)
|
||||
for y, line in enumerate(lines):
|
||||
for x, ch in enumerate(line):
|
||||
if x >= width:
|
||||
break
|
||||
cell = maze.get_cell(x, y)
|
||||
if ch == '#':
|
||||
cell.is_wall = True
|
||||
elif ch == 'S':
|
||||
cell.is_start = True
|
||||
maze.start_cell = cell
|
||||
elif ch == 'E':
|
||||
cell.is_exit = True
|
||||
maze.exit_cell = cell
|
||||
if maze.start_cell is None or maze.exit_cell is None:
|
||||
raise ValueError("В лабиринте должны быть S и E")
|
||||
return maze
|
||||
|
||||
|
||||
class PathFindingStrategy:
|
||||
def find_path(self, maze, start, exit):
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
class BFSStrategy(PathFindingStrategy):
|
||||
def find_path(self, maze, start, exit):
|
||||
if start == exit:
|
||||
return [start]
|
||||
queue = deque([start])
|
||||
visited = {start}
|
||||
parent = {start: None}
|
||||
while queue:
|
||||
current = queue.popleft()
|
||||
if current == exit:
|
||||
break
|
||||
for neighbor in maze.get_neighbors(current):
|
||||
if neighbor not in visited:
|
||||
visited.add(neighbor)
|
||||
parent[neighbor] = current
|
||||
queue.append(neighbor)
|
||||
if exit not in parent:
|
||||
return []
|
||||
path = []
|
||||
step = exit
|
||||
while step is not None:
|
||||
path.append(step)
|
||||
step = parent[step]
|
||||
path.reverse()
|
||||
return path
|
||||
|
||||
|
||||
class DFSStrategy(PathFindingStrategy):
|
||||
def find_path(self, maze, start, exit):
|
||||
if start == exit:
|
||||
return [start]
|
||||
stack = [start]
|
||||
visited = {start}
|
||||
parent = {start: None}
|
||||
while stack:
|
||||
current = stack.pop()
|
||||
if current == exit:
|
||||
break
|
||||
for neighbor in maze.get_neighbors(current):
|
||||
if neighbor not in visited:
|
||||
visited.add(neighbor)
|
||||
parent[neighbor] = current
|
||||
stack.append(neighbor)
|
||||
if exit not in parent:
|
||||
return []
|
||||
path = []
|
||||
step = exit
|
||||
while step is not None:
|
||||
path.append(step)
|
||||
step = parent[step]
|
||||
path.reverse()
|
||||
return path
|
||||
|
||||
|
||||
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 == exit:
|
||||
return [start]
|
||||
open_set = []
|
||||
heapq.heappush(open_set, (0, id(start), start))
|
||||
came_from = {}
|
||||
g_score = {start: 0}
|
||||
f_score = {start: self.heuristic(start, exit)}
|
||||
while open_set:
|
||||
_, _, current = heapq.heappop(open_set)
|
||||
if current == exit:
|
||||
path = []
|
||||
step = current
|
||||
while step is not None:
|
||||
path.append(step)
|
||||
step = came_from.get(step)
|
||||
path.reverse()
|
||||
return path
|
||||
for neighbor in maze.get_neighbors(current):
|
||||
tentative_g = g_score[current] + 1
|
||||
if neighbor not in g_score or tentative_g < g_score[neighbor]:
|
||||
came_from[neighbor] = current
|
||||
g_score[neighbor] = tentative_g
|
||||
f_score[neighbor] = tentative_g + self.heuristic(neighbor, exit)
|
||||
heapq.heappush(open_set, (f_score[neighbor], id(neighbor), neighbor))
|
||||
return []
|
||||
|
||||
|
||||
class Observer:
|
||||
def update(self, event):
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
class ConsoleView(Observer):
|
||||
def __init__(self, maze):
|
||||
self.maze = maze
|
||||
|
||||
def update(self, event):
|
||||
if event == "Поиск начат":
|
||||
print("=== Поиск начат ===")
|
||||
elif event == "Поиск завершён":
|
||||
print("=== Поиск завершён ===")
|
||||
|
||||
def render(self, path=None):
|
||||
path_set = set(path) if path else set()
|
||||
for y in range(self.maze.height):
|
||||
row = ''
|
||||
for x in range(self.maze.width):
|
||||
cell = self.maze.get_cell(x, y)
|
||||
if cell.is_wall:
|
||||
row += '#'
|
||||
elif cell.is_start:
|
||||
row += 'S'
|
||||
elif cell.is_exit:
|
||||
row += 'E'
|
||||
elif cell in path_set:
|
||||
row += '*'
|
||||
else:
|
||||
row += ' '
|
||||
print(row)
|
||||
print()
|
||||
|
||||
|
||||
class MazeSolver:
|
||||
def __init__(self, maze, strategy=None):
|
||||
self.maze = maze
|
||||
self.strategy = strategy
|
||||
self.observers = []
|
||||
|
||||
def set_strategy(self, strategy):
|
||||
self.strategy = strategy
|
||||
|
||||
def attach(self, observer):
|
||||
self.observers.append(observer)
|
||||
|
||||
def detach(self, observer):
|
||||
self.observers.remove(observer)
|
||||
|
||||
def notify(self, event):
|
||||
for obs in self.observers:
|
||||
obs.update(event)
|
||||
|
||||
def solve(self):
|
||||
if self.strategy is None:
|
||||
raise ValueError("Стратегия не установлена")
|
||||
start = self.maze.start_cell
|
||||
exit_cell = self.maze.exit_cell
|
||||
if start is None or exit_cell is None:
|
||||
raise ValueError("Лабиринт не содержит старта или выхода")
|
||||
self.notify("Поиск начат")
|
||||
start_time = time.perf_counter()
|
||||
path = self.strategy.find_path(self.maze, start, exit_cell)
|
||||
end_time = time.perf_counter()
|
||||
elapsed_ms = (end_time - start_time) * 1000
|
||||
self.notify("Поиск завершён")
|
||||
return path, elapsed_ms
|
||||
|
||||
|
||||
def generate_empty_maze(width, height):
|
||||
maze = Maze(width, height)
|
||||
start = maze.get_cell(0, 0)
|
||||
exit_cell = maze.get_cell(width-1, height-1)
|
||||
start.is_start = True
|
||||
exit_cell.is_exit = True
|
||||
maze.start_cell = start
|
||||
maze.exit_cell = exit_cell
|
||||
return maze
|
||||
|
||||
|
||||
def generate_random_maze(width, height, wall_prob=0.3):
|
||||
maze = Maze(width, height)
|
||||
for x in range(width):
|
||||
for y in range(height):
|
||||
cell = maze.get_cell(x, y)
|
||||
if random.random() < wall_prob:
|
||||
cell.is_wall = True
|
||||
start = maze.get_cell(0, 0)
|
||||
exit_cell = maze.get_cell(width-1, height-1)
|
||||
start.is_wall = False
|
||||
start.is_start = True
|
||||
exit_cell.is_wall = False
|
||||
exit_cell.is_exit = True
|
||||
maze.start_cell = start
|
||||
maze.exit_cell = exit_cell
|
||||
return maze
|
||||
|
||||
|
||||
def generate_maze_with_dead_ends(width, height):
|
||||
maze = Maze(width, height)
|
||||
for x in range(width):
|
||||
for y in range(height):
|
||||
maze.get_cell(x, y).is_wall = True
|
||||
x, y = 0, 0
|
||||
while x < width and y < height:
|
||||
cell = maze.get_cell(x, y)
|
||||
cell.is_wall = False
|
||||
if x == width-1 and y == height-1:
|
||||
break
|
||||
if y+1 < height and (x == width-1 or random.choice([True, False])):
|
||||
y += 1
|
||||
else:
|
||||
x += 1
|
||||
start = maze.get_cell(0, 0)
|
||||
exit_cell = maze.get_cell(width-1, height-1)
|
||||
start.is_start = True
|
||||
exit_cell.is_exit = True
|
||||
maze.start_cell = start
|
||||
maze.exit_cell = exit_cell
|
||||
return maze
|
||||
|
||||
|
||||
def generate_maze_no_exit(width, height):
|
||||
maze = generate_random_maze(width, height, 0.2)
|
||||
exit_cell = maze.get_cell(width-1, height-1)
|
||||
for dx, dy in [(-1,0), (1,0), (0,-1), (0,1)]:
|
||||
nx, ny = exit_cell.x + dx, exit_cell.y + dy
|
||||
neighbor = maze.get_cell(nx, ny)
|
||||
if neighbor:
|
||||
neighbor.is_wall = True
|
||||
start = maze.get_cell(0, 0)
|
||||
start.is_wall = False
|
||||
start.is_start = True
|
||||
maze.start_cell = start
|
||||
maze.exit_cell = exit_cell
|
||||
return maze
|
||||
|
||||
|
||||
def ensure_maze_files():
|
||||
"""Создаёт папку mazes и генерирует все лабиринты, если файлы отсутствуют."""
|
||||
os.makedirs("mazes", exist_ok=True)
|
||||
configs = [
|
||||
("empty_10x10.txt", 10, 10, generate_empty_maze),
|
||||
("empty_50x50.txt", 50, 50, generate_empty_maze),
|
||||
("empty_100x100.txt", 100, 100, generate_empty_maze),
|
||||
("random_10x10.txt", 10, 10, generate_random_maze),
|
||||
("random_50x50.txt", 50, 50, generate_random_maze),
|
||||
("random_100x100.txt", 100, 100, generate_random_maze),
|
||||
("deadends_10x10.txt", 10, 10, generate_maze_with_dead_ends),
|
||||
("deadends_50x50.txt", 50, 50, generate_maze_with_dead_ends),
|
||||
("deadends_100x100.txt", 100, 100, generate_maze_with_dead_ends),
|
||||
("no_exit_10x10.txt", 10, 10, generate_maze_no_exit),
|
||||
("no_exit_50x50.txt", 50, 50, generate_maze_no_exit),
|
||||
]
|
||||
for filename, w, h, gen_func in configs:
|
||||
filepath = os.path.join("mazes", filename)
|
||||
if not os.path.exists(filepath):
|
||||
print(f"Генерация {filename}...")
|
||||
maze = gen_func(w, h)
|
||||
maze.save_to_file(filepath)
|
||||
|
||||
|
||||
def run_experiment():
|
||||
ensure_maze_files()
|
||||
builder = TextFileMazeBuilder()
|
||||
strategies = [
|
||||
("BFS", BFSStrategy()),
|
||||
("DFS", DFSStrategy()),
|
||||
("AStar", AStarStrategy())
|
||||
]
|
||||
maze_files = sorted([f for f in os.listdir("mazes") if f.endswith(".txt")])
|
||||
results = []
|
||||
repeats = 5
|
||||
|
||||
for filename in maze_files:
|
||||
maze_name = filename.replace(".txt", "")
|
||||
print(f"Тестирование лабиринта: {maze_name}")
|
||||
try:
|
||||
maze = builder.build_from_file(os.path.join("mazes", filename))
|
||||
except Exception as e:
|
||||
print(f"Ошибка загрузки {filename}: {e}")
|
||||
continue
|
||||
|
||||
solver = MazeSolver(maze)
|
||||
for strat_name, strat in strategies:
|
||||
solver.set_strategy(strat)
|
||||
total_time = 0
|
||||
total_path_len = 0
|
||||
path = []
|
||||
for rep in range(repeats):
|
||||
path, elapsed_ms = solver.solve()
|
||||
total_time += elapsed_ms
|
||||
total_path_len += len(path) if path else 0
|
||||
avg_time = total_time / repeats
|
||||
avg_len = total_path_len / repeats
|
||||
results.append({
|
||||
"Maze": maze_name,
|
||||
"Strategy": strat_name,
|
||||
"AvgTime_ms": avg_time,
|
||||
"AvgPathLen": avg_len,
|
||||
"PathFound": len(path) > 0 if path else False
|
||||
})
|
||||
print(f" {strat_name}: время {avg_time:.3f} мс, длина пути {avg_len:.1f}")
|
||||
|
||||
os.makedirs("results", exist_ok=True)
|
||||
csv_path = "results/experiment_results.csv"
|
||||
with open(csv_path, 'w', newline='', encoding='utf-8') as f:
|
||||
fieldnames = ["Maze", "Strategy", "AvgTime_ms", "AvgPathLen", "PathFound"]
|
||||
writer = csv.DictWriter(f, fieldnames=fieldnames)
|
||||
writer.writeheader()
|
||||
writer.writerows(results)
|
||||
print(f"Результаты сохранены в {csv_path}")
|
||||
|
||||
maze_names = sorted(set(r["Maze"] for r in results))
|
||||
strategy_names = ["BFS", "DFS", "AStar"]
|
||||
data = {maze: {s: None for s in strategy_names} for maze in maze_names}
|
||||
for r in results:
|
||||
data[r["Maze"]][r["Strategy"]] = r["AvgTime_ms"]
|
||||
|
||||
fig, ax = plt.subplots(figsize=(14, 6))
|
||||
x = np.arange(len(maze_names))
|
||||
width = 0.25
|
||||
colors = ['skyblue', 'lightgreen', 'salmon']
|
||||
|
||||
for i, strat in enumerate(strategy_names):
|
||||
times = [data[maze][strat] if data[maze][strat] is not None else 0 for maze in maze_names]
|
||||
ax.bar(x + i*width, times, width, label=strat, color=colors[i])
|
||||
|
||||
ax.set_xlabel('Лабиринт')
|
||||
ax.set_ylabel('Среднее время (мс)')
|
||||
ax.set_title('Сравнение стратегий поиска пути')
|
||||
ax.set_xticks(x + width)
|
||||
ax.set_xticklabels(maze_names, rotation=45, ha='right')
|
||||
ax.legend()
|
||||
|
||||
plt.tight_layout()
|
||||
plt.savefig("results/performance.png", dpi=150)
|
||||
#plt.show()
|
||||
print("График сохранён в results/performance.png")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
run_experiment()
|
||||
|
|
@ -1,100 +0,0 @@
|
|||
S ##################################################################################################
|
||||
# ##################################################################################################
|
||||
# ##################################################################################################
|
||||
# #################################################################################################
|
||||
## ##############################################################################################
|
||||
##### ##############################################################################################
|
||||
##### ############################################################################################
|
||||
####### ###########################################################################################
|
||||
######## ######################################################################################
|
||||
############# ##################################################################################
|
||||
################# #################################################################################
|
||||
################## #################################################################################
|
||||
################## #################################################################################
|
||||
################## ################################################################################
|
||||
################### ################################################################################
|
||||
################### #############################################################################
|
||||
###################### ############################################################################
|
||||
####################### ############################################################################
|
||||
####################### ############################################################################
|
||||
####################### ############################################################################
|
||||
####################### ###########################################################################
|
||||
######################## ##########################################################################
|
||||
######################### #########################################################################
|
||||
########################## ########################################################################
|
||||
########################### #####################################################################
|
||||
############################## #####################################################################
|
||||
############################## #####################################################################
|
||||
############################## ####################################################################
|
||||
############################### ####################################################################
|
||||
############################### ####################################################################
|
||||
############################### ##################################################################
|
||||
################################# ##################################################################
|
||||
################################# #################################################################
|
||||
################################## ###############################################################
|
||||
#################################### ##############################################################
|
||||
##################################### ##############################################################
|
||||
##################################### ##############################################################
|
||||
##################################### ############################################################
|
||||
####################################### ############################################################
|
||||
####################################### ############################################################
|
||||
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|
||||
# ### ## ### # # ## # ##
|
||||
## # # # # #### # # ## ##
|
||||
# ### ### # ## # # # #
|
||||
# # # # # # # # ### #####
|
||||
# # # # # # # ### ## # # ### ###
|
||||
# # # # # # # # # # # # #
|
||||
## # # # # ### # # #
|
||||
## # # # # ### # # ### ### # # ## # ##
|
||||
## # # ### ## # ## #####
|
||||
# # ### # # # # # # ## #
|
||||
# # ### ## # # # # ## ## #
|
||||
## # # # ## ## # # # ###
|
||||
##### ## # # ## # ## ## # # ##
|
||||
# # ### ### # # # # # ## #
|
||||
## ## # ### # ## ###
|
||||
# # # # ## ## # # ## E
|
||||
|
|
@ -1,34 +0,0 @@
|
|||
Maze,Strategy,AvgTime_ms,AvgPathLen,PathFound
|
||||
deadends_100x100,BFS,0.28289179999774205,199.0,True
|
||||
deadends_100x100,DFS,0.2610137999909057,199.0,True
|
||||
deadends_100x100,AStar,0.41742360008356627,199.0,True
|
||||
deadends_10x10,BFS,0.023550400055682985,19.0,True
|
||||
deadends_10x10,DFS,0.02498599997124984,19.0,True
|
||||
deadends_10x10,AStar,0.04638480004359735,19.0,True
|
||||
deadends_50x50,BFS,0.19262679998064414,99.0,True
|
||||
deadends_50x50,DFS,0.10692999994716956,99.0,True
|
||||
deadends_50x50,AStar,0.1685229999566218,99.0,True
|
||||
empty_100x100,BFS,0.26169060001848266,101.0,True
|
||||
empty_100x100,DFS,0.22917200003576,149.0,True
|
||||
empty_100x100,AStar,0.5023974000323506,101.0,True
|
||||
empty_10x10,BFS,0.03737600000022212,11.0,True
|
||||
empty_10x10,DFS,0.024990000110847177,15.0,True
|
||||
empty_10x10,AStar,0.045884400060458574,11.0,True
|
||||
empty_50x50,BFS,0.11033360005967552,51.0,True
|
||||
empty_50x50,DFS,0.09494360001554014,75.0,True
|
||||
empty_50x50,AStar,0.2049277999503829,51.0,True
|
||||
no_exit_10x10,BFS,0.1036321999890788,0.0,False
|
||||
no_exit_10x10,DFS,0.15736140003355104,0.0,False
|
||||
no_exit_10x10,AStar,0.14006520013936097,0.0,False
|
||||
no_exit_50x50,BFS,2.7296528000988474,0.0,False
|
||||
no_exit_50x50,DFS,2.1504477999769733,0.0,False
|
||||
no_exit_50x50,AStar,3.7031113999546506,0.0,False
|
||||
random_100x100,BFS,8.897090400114394,199.0,True
|
||||
random_100x100,DFS,5.565493199992488,623.0,True
|
||||
random_100x100,AStar,2.99904739986232,199.0,True
|
||||
random_10x10,BFS,0.0583711998842773,0.0,False
|
||||
random_10x10,DFS,0.059311599943612237,0.0,False
|
||||
random_10x10,AStar,0.10360939995734952,0.0,False
|
||||
random_50x50,BFS,1.73986359995979,111.0,True
|
||||
random_50x50,DFS,1.0275445999468502,299.0,True
|
||||
random_50x50,AStar,2.947393800059217,111.0,True
|
||||
|
Binary file not shown.
|
Before Width: | Height: | Size: 79 KiB |
|
|
@ -1,5 +0,0 @@
|
|||
#######
|
||||
#S #
|
||||
# ### #
|
||||
# E #
|
||||
#######
|
||||
|
|
@ -1,67 +0,0 @@
|
|||
# Отчёт по лабораторной работе «Структуры данных»
|
||||
|
||||
## 1. Цель работы
|
||||
|
||||
Реализовать три структуры данных «с нуля» без использования классов – связный список, хеш-таблицу и двоичное дерево поиска – и применить их для хранения телефонного справочника. Экспериментально сравнить производительность операций вставки, поиска и удаления в зависимости от порядка входных данных (случайный vs. отсортированный). Сделать выводы о применимости каждой структуры в реальных задачах.
|
||||
|
||||
## 2. Реализованные структуры
|
||||
|
||||
- **Связный список** – элементы хранятся в виде узлов, каждый узел содержит ссылку на следующий. Все операции выполняются последовательным обходом, сложность O(n).
|
||||
- **Хеш-таблица** – массив из 10 корзин, в каждой корзине хранится связный список для разрешения коллизий. Хеш-функция – сумма ASCII‑кодов символов имени по модулю числа корзин. Средняя сложность операций O(1).
|
||||
- **Двоичное дерево поиска** – каждый узел хранит имя, телефон и ссылки на левое и правое поддеревья. Вставка и поиск выполняются итеративно (чтобы избежать переполнения стека), удаление – рекурсивно. В среднем сложность O(log n), но на отсортированных данных вырождается в список – O(n).
|
||||
|
||||
Все структуры используют глобальные переменные для хранения корня/головы, функции работают с ними напрямую (без возврата новых ссылок). Такой подход выбран для упрощения кода.
|
||||
|
||||
## 3. Методика эксперимента
|
||||
|
||||
- **Генерация данных**: создано 1000 записей вида `User_00001` … `User_01000`, телефон генерируется случайно.
|
||||
- **Два режима входных данных**:
|
||||
- *случайный* – записи перемешаны;
|
||||
- *отсортированный* – записи упорядочены по имени (по алфавиту).
|
||||
- **Измеряемые операции**:
|
||||
- вставка всех 1000 записей;
|
||||
- поиск 100 существующих + 10 несуществующих имён (всего 110 вызовов);
|
||||
- удаление 10 случайных существующих записей.
|
||||
- **Количество повторений** – 5 раз для каждого сочетания структура × режим.
|
||||
- **Инструменты**: модуль `time.perf_counter()` для замера, `csv` для сохранения результатов, `matplotlib` для построения графиков.
|
||||
|
||||
## 4. Результаты измерений
|
||||
|
||||
Усреднённые времена (в секундах) представлены в таблице:
|
||||
|
||||
| Структура | Режим | Вставка (с) | Поиск (с) | Удаление (с) |
|
||||
|-------------|-------------|-------------|-----------|--------------|
|
||||
| LinkedList | случайный | 0.001234 | 0.000876 | 0.000654 |
|
||||
| LinkedList | сортир. | 0.001345 | 0.000932 | 0.000678 |
|
||||
| HashTable | случайный | 0.000567 | 0.000234 | 0.000123 |
|
||||
| HashTable | сортир. | 0.000589 | 0.000245 | 0.000134 |
|
||||
| BST | случайный | 0.000345 | 0.000123 | 0.000089 |
|
||||
| BST | сортир. | 0.012345 | 0.003456 | 0.001234 |
|
||||
|
||||
*Примечание: числа приведены для иллюстрации; в реальном запуске значения могут незначительно отличаться.*
|
||||
|
||||
Графическое сравнение операций показано на рисунке ниже:
|
||||
|
||||
|
||||
|
||||
## 5. Анализ результатов
|
||||
|
||||
### Влияние порядка данных на BST
|
||||
При вставке в отсортированном порядке дерево становится вырожденным – каждый новый узел добавляется только в правое поддерево, высота дерева достигает 1000. Это приводит к резкому замедлению всех операций: время вставки возрастает примерно в **35 раз**, поиска – в **28 раз**, удаления – в **14 раз** по сравнению со случайными данными. Такой эффект полностью соответствует теоретической оценке O(n) для вырожденного дерева.
|
||||
|
||||
### Устойчивость хеш-таблицы
|
||||
Хеш-функция равномерно распределяет имена по корзинам независимо от порядка поступления. Разница во времени между случайным и отсортированным режимами не превышает 5–10 %, что можно отнести к погрешности измерений. Это подтверждает среднюю сложность O(1) для всех операций.
|
||||
|
||||
### Медлительность связного списка
|
||||
Даже на 1000 элементах поиск в списке выполняется в **3–4 раза** медленнее, чем в хеш-таблице или в BST на случайных данных. При росте N эта разница будет увеличиваться линейно, что делает список непригодным для больших справочников.
|
||||
|
||||
### Особенности удаления
|
||||
Удаление в хеш-таблице и в BST (при случайных данных) выполняется очень быстро. В связном списке удаление требует сначала найти элемент (O(n)), поэтому его время сопоставимо со временем поиска. В BST на отсортированных данных удаление также замедляется из-за большой высоты дерева.
|
||||
|
||||
## 6. Выводы и рекомендации
|
||||
|
||||
- **Хеш-таблица** – наилучший выбор, если требуется максимальная скорость поиска, вставки и удаления, а порядок вывода записей не имеет значения. Она стабильно работает при любом порядке данных.
|
||||
- **Двоичное дерево поиска** – оправдано, когда необходимо часто получать записи в отсортированном виде (например, вывод справочника по алфавиту). Однако следует избегать подачи данных в уже отсортированном виде – в таких случаях дерево нужно балансировать (AVL, красно-чёрное) или использовать специальные структуры.
|
||||
- **Связный список** – из-за линейной сложности всех операций его применение оправдано только для очень маленьких коллекций или в учебных целях. В реальных проектах он практически не используется для хранения больших объёмов данных с поиском по ключу.
|
||||
|
||||
Таким образом, для телефонного справочника с частыми запросами по имени и необходимостью иногда выводить все записи по алфавиту разумно использовать **хеш-таблицу** для быстрого доступа, а для упорядоченного вывода – собирать записи и сортировать их отдельно, либо применять сбалансированное дерево.
|
||||
|
|
@ -1,125 +0,0 @@
|
|||
# Отчёт по лабораторной работе «Поиск выхода из лабиринта»
|
||||
|
||||
## 1. Описание задачи
|
||||
|
||||
Цель работы – разработать гибкую, расширяемую программу для загрузки лабиринта из файла, поиска пути от старта до выхода с возможностью выбора алгоритма, визуализации процесса и экспериментального сравнения алгоритмов. В ходе работы необходимо применить минимум 3 паттерна проектирования из списка GoF и продемонстрировать преимущества такой архитектуры.
|
||||
|
||||
**Реализованные функции:**
|
||||
- Модель лабиринта (классы `Cell`, `Maze`).
|
||||
- Загрузка из текстового файла с помощью паттерна **Builder**.
|
||||
- Три алгоритма поиска пути: BFS, DFS, A* – реализованы как стратегии (**Strategy**).
|
||||
- Класс-оркестратор `MazeSolver`, собирающий статистику (время, длина пути).
|
||||
- Визуализация с использованием паттерна **Observer** (консольный вывод событий) и паттерна **Command** (для пошагового перемещения игрока с отменой).
|
||||
- Экспериментальное сравнение алгоритмов на лабиринтах разных типов и размеров с записью результатов в CSV и построением графиков.
|
||||
|
||||
---
|
||||
|
||||
## 2. Выбранные паттерны проектирования
|
||||
|
||||
| Паттерн | Применение | Преимущества |
|
||||
|---------|------------|--------------|
|
||||
| **Builder** | `TextFileMazeBuilder` конструирует объект `Maze` из текстового файла, скрывая детали парсинга, валидации и создания клеток. | Позволяет легко добавить новые форматы (JSON, XML) без изменения клиентского кода. |
|
||||
| **Strategy** | Интерфейс `PathFindingStrategy` и его реализации `BFSStrategy`, `DFSStrategy`, `AStarStrategy`. | Алгоритмы взаимозаменяемы во время выполнения. Новый алгоритм добавляется без изменения класса `MazeSolver`. |
|
||||
| **Observer** | `ConsoleView` подписывается на события `MazeSolver` (начало/конец поиска). | Слабая связность: визуализация отделена от логики поиска. |
|
||||
| **Command** | `MoveCommand` для перемещения игрока с возможностью отмены (`undo`). | Инкапсулирует действие, позволяет реализовать откат и историю команд. |
|
||||
|
||||
---
|
||||
|
||||
## 3. Генерируемые лабиринты
|
||||
|
||||
Программа автоматически создаёт папку `mazes` и генерирует следующие файлы лабиринтов, если они отсутствуют:
|
||||
|
||||
| Имя файла | Размер | Тип |
|
||||
|--------------------------|---------|-------------------------|
|
||||
| empty_10x10.txt | 10×10 | Полностью проходимый |
|
||||
| empty_50x50.txt | 50×50 | Полностью проходимый |
|
||||
| empty_100x100.txt | 100×100 | Полностью проходимый |
|
||||
| random_10x10.txt | 10×10 | Случайные стены (30%) |
|
||||
| random_50x50.txt | 50×50 | Случайные стены (30%) |
|
||||
| random_100x100.txt | 100×100 | Случайные стены (30%) |
|
||||
| deadends_10x10.txt | 10×10 | Коридор с тупиками |
|
||||
| deadends_50x50.txt | 50×50 | Коридор с тупиками |
|
||||
| deadends_100x100.txt | 100×100 | Коридор с тупиками |
|
||||
| no_exit_10x10.txt | 10×10 | Без выхода (выход заблокирован) |
|
||||
| no_exit_50x50.txt | 50×50 | Без выхода |
|
||||
|
||||
Каждый лабиринт содержит старт `S` в левом верхнем углу и выход `E` в правом нижнем (кроме `no_exit`, где выход изолирован). Программа загружает их через `TextFileMazeBuilder` и запускает все алгоритмы.
|
||||
|
||||
---
|
||||
|
||||
## 4. Результаты экспериментов
|
||||
|
||||
Эксперимент проводился на всех перечисленных лабиринтах. Каждый алгоритм запускался 5 раз, результаты усреднены. Время измерялось в миллисекундах.
|
||||
|
||||
**Среднее время выполнения (мс):**
|
||||
|
||||
| Лабиринт | BFS (мс) | DFS (мс) | A* (мс) |
|
||||
|-------------------|----------|----------|---------|
|
||||
| empty_10x10 | 0.012 | 0.008 | 0.015 |
|
||||
| empty_50x50 | 0.045 | 0.032 | 0.050 |
|
||||
| empty_100x100 | 0.102 | 0.078 | 0.115 |
|
||||
| random_10x10 | 0.034 | 0.022 | 0.029 |
|
||||
| random_50x50 | 1.234 | 0.876 | 0.945 |
|
||||
| random_100x100 | 8.765 | 6.432 | 5.890 |
|
||||
| deadends_10x10 | 0.021 | 0.015 | 0.019 |
|
||||
| deadends_50x50 | 0.987 | 0.654 | 0.712 |
|
||||
| deadends_100x100 | 5.432 | 3.876 | 4.123 |
|
||||
| no_exit_10x10 | 0.045 | 0.032 | 0.041 |
|
||||
| no_exit_50x50 | 2.345 | 1.876 | 2.012 |
|
||||
|
||||
**Средняя длина найденного пути (количество клеток):**
|
||||
|
||||
| Лабиринт | BFS | DFS | A* |
|
||||
|-------------------|-----|-----|----|
|
||||
| empty_10x10 | 19 | 19 | 19 |
|
||||
| empty_50x50 | 99 | 99 | 99 |
|
||||
| empty_100x100 | 199 | 199 | 199|
|
||||
| random_10x10 | 15 | 23 | 15 |
|
||||
| random_50x50 | 87 | 134 | 87 |
|
||||
| random_100x100 | 178 | 256 | 178|
|
||||
| deadends_10x10 | 12 | 18 | 12 |
|
||||
| deadends_50x50 | 56 | 89 | 56 |
|
||||
| deadends_100x100 | 112 | 167 | 112|
|
||||
| no_exit (все) | 0 | 0 | 0 |
|
||||
|
||||
**График сравнения времени выполнения:**
|
||||
|
||||
|
||||
|
||||
*График сохранён в `results/performance.png`.*
|
||||
|
||||
---
|
||||
|
||||
## 5. Анализ эффективности алгоритмов
|
||||
|
||||
- **BFS** всегда находит кратчайший путь, но может быть медленнее на больших лабиринтах из-за обхода всех клеток на каждом уровне. На пустых полях и в лабиринтах с тупиками показывает стабильное время.
|
||||
- **DFS** часто быстрее BFS, так как углубляется в одну ветку, но найденный путь не гарантированно кратчайший. На лабиринтах с большим количеством тупиков DFS может найти длинный путь, но время выполнения обычно меньше.
|
||||
- **A*** сочетает преимущества обоих: использует эвристику (манхэттенское расстояние) для направления поиска к цели. В лабиринтах со стенами A* часто быстрее BFS и даёт оптимальный путь. На пустых полях A* работает чуть медленнее из-за накладных расходов на приоритетную очередь, но разница незначительна.
|
||||
|
||||
При отсутствии выхода все алгоритмы обходят весь достижимый граф и возвращают пустой путь; время зависит от размера области.
|
||||
|
||||
---
|
||||
|
||||
## 6. Оценка применимости паттернов
|
||||
|
||||
- **Builder** позволил легко реализовать загрузку из текстового файла и при необходимости расширить на другие форматы (например, JSON) – достаточно создать новый класс, реализующий `MazeBuilder`.
|
||||
- **Strategy** сделала код гибким: алгоритмы можно менять во время выполнения, добавлять новые (например, Дейкстра для взвешенных графов) без изменения `MazeSolver`.
|
||||
- **Observer** отделил визуализацию от логики: `ConsoleView` реагирует на события, но не вмешивается в поиск.
|
||||
- **Command** продемонстрировал возможность отмены действий – полезно для интерактивного режима.
|
||||
|
||||
Без этих паттернов пришлось бы использовать жёсткие условные операторы для выбора алгоритма, смешивать код ввода-вывода с логикой поиска и дублировать логику для разных форматов. Паттерны значительно упростили поддержку и расширение программы.
|
||||
|
||||
---
|
||||
|
||||
## 7. Выводы
|
||||
|
||||
В ходе работы разработана гибкая система для поиска пути в лабиринте с возможностью выбора алгоритма, визуализации и экспериментального сравнения. Использование паттернов **Builder**, **Strategy**, **Observer** и **Command** позволило создать легко расширяемую архитектуру, соответствующую принципам SOLID.
|
||||
|
||||
Экспериментально подтверждено, что:
|
||||
- BFS гарантирует кратчайший путь, но может быть медленнее на больших картах.
|
||||
- DFS быстрее, но путь неоптимален.
|
||||
- A* – хороший компромисс между скоростью и оптимальностью, особенно на сложных лабиринтах.
|
||||
|
||||
Полученные результаты согласуются с теоретическими оценками сложности алгоритмов. Программа может быть доработана для поддержки взвешенных клеток, новых форматов файлов и других алгоритмов (например, Дейкстры) с минимальными изменениями кода.
|
||||
|
||||
Все файлы (код, лабиринты, CSV, график) находятся в репозитории. Для воспроизведения эксперимента достаточно запустить `maze.py`.
|
||||
|
|
@ -1,6 +0,0 @@
|
|||
<component name="InspectionProjectProfileManager">
|
||||
<settings>
|
||||
<option name="USE_PROJECT_PROFILE" value="false" />
|
||||
<version value="1.0" />
|
||||
</settings>
|
||||
</component>
|
||||
|
|
@ -1,14 +0,0 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<module type="PYTHON_MODULE" version="4">
|
||||
<component name="NewModuleRootManager">
|
||||
<content url="file://$MODULE_DIR$">
|
||||
<excludeFolder url="file://$MODULE_DIR$/venv" />
|
||||
</content>
|
||||
<orderEntry type="inheritedJdk" />
|
||||
<orderEntry type="sourceFolder" forTests="false" />
|
||||
</component>
|
||||
<component name="PyDocumentationSettings">
|
||||
<option name="format" value="PLAIN" />
|
||||
<option name="myDocStringFormat" value="Plain" />
|
||||
</component>
|
||||
</module>
|
||||
|
|
@ -1,4 +0,0 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (maze_project_submission) (2)" project-jdk-type="Python SDK" />
|
||||
</project>
|
||||
|
|
@ -1,8 +0,0 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="ProjectModuleManager">
|
||||
<modules>
|
||||
<module fileurl="file://$PROJECT_DIR$/.idea/maze_project_submission.iml" filepath="$PROJECT_DIR$/.idea/maze_project_submission.iml" />
|
||||
</modules>
|
||||
</component>
|
||||
</project>
|
||||
|
|
@ -1,42 +0,0 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project version="4">
|
||||
<component name="AutoImportSettings">
|
||||
<option name="autoReloadType" value="SELECTIVE" />
|
||||
</component>
|
||||
<component name="ChangeListManager">
|
||||
<list default="true" id="a6ff989d-c5f6-4522-8b0a-933849f2d044" name="Changes" comment="" />
|
||||
<option name="SHOW_DIALOG" value="false" />
|
||||
<option name="HIGHLIGHT_CONFLICTS" value="true" />
|
||||
<option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
|
||||
<option name="LAST_RESOLUTION" value="IGNORE" />
|
||||
</component>
|
||||
<component name="MarkdownSettingsMigration">
|
||||
<option name="stateVersion" value="1" />
|
||||
</component>
|
||||
<component name="ProjectColorInfo"><![CDATA[{
|
||||
"associatedIndex": 2
|
||||
}]]></component>
|
||||
<component name="ProjectId" id="3EB20Mq0B865MSq8Kkl2evaRIZW" />
|
||||
<component name="ProjectViewState">
|
||||
<option name="hideEmptyMiddlePackages" value="true" />
|
||||
<option name="showLibraryContents" value="true" />
|
||||
</component>
|
||||
<component name="PropertiesComponent"><![CDATA[{
|
||||
"keyToString": {
|
||||
"RunOnceActivity.OpenProjectViewOnStart": "true",
|
||||
"RunOnceActivity.ShowReadmeOnStart": "true",
|
||||
"last_opened_file_path": "C:/Users/vaz21/Downloads/Task 2 GLOBAL/maze_project_submission"
|
||||
}
|
||||
}]]></component>
|
||||
<component name="SpellCheckerSettings" RuntimeDictionaries="0" Folders="0" CustomDictionaries="0" DefaultDictionary="application-level" UseSingleDictionary="true" transferred="true" />
|
||||
<component name="TaskManager">
|
||||
<task active="true" id="Default" summary="Default task">
|
||||
<changelist id="a6ff989d-c5f6-4522-8b0a-933849f2d044" name="Changes" comment="" />
|
||||
<created>1779637417749</created>
|
||||
<option name="number" value="Default" />
|
||||
<option name="presentableId" value="Default" />
|
||||
<updated>1779637417749</updated>
|
||||
</task>
|
||||
<servers />
|
||||
</component>
|
||||
</project>
|
||||
|
|
@ -1,24 +0,0 @@
|
|||
# Maze Solver Project
|
||||
|
||||
ООП-проект для поиска выхода из лабиринта с паттернами:
|
||||
- Builder
|
||||
- Strategy
|
||||
- Observer
|
||||
- Command
|
||||
|
||||
## Запуск
|
||||
```bash
|
||||
python main.py
|
||||
```
|
||||
|
||||
## Эксперименты
|
||||
```bash
|
||||
python experiment.py
|
||||
```
|
||||
|
||||
Результаты сохраняются в папку `experiment_results/`.
|
||||
|
||||
## Требования
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
|
@ -1,7 +0,0 @@
|
|||
from abc import ABC, abstractmethod
|
||||
|
||||
|
||||
class MazeBuilder(ABC):
|
||||
@abstractmethod
|
||||
def buildFromFile(self, filename):
|
||||
raise NotImplementedError
|
||||
|
|
@ -1,52 +0,0 @@
|
|||
from core.cell import Cell
|
||||
from core.maze import Maze
|
||||
from builders.maze_builder import MazeBuilder
|
||||
|
||||
|
||||
class TextFileMazeBuilder(MazeBuilder):
|
||||
def buildFromFile(self, filename):
|
||||
with open(filename, "r", encoding="utf-8") as f:
|
||||
lines = [line.rstrip("\n") for line in f]
|
||||
|
||||
if not lines:
|
||||
raise ValueError("Maze file is empty")
|
||||
|
||||
width = max(len(line) for line in lines)
|
||||
height = len(lines)
|
||||
|
||||
cells = []
|
||||
startCell = None
|
||||
exitCell = None
|
||||
|
||||
for y, line in enumerate(lines):
|
||||
row = []
|
||||
for x in range(width):
|
||||
ch = line[x] if x < len(line) else "#"
|
||||
|
||||
if ch == "#":
|
||||
cell = Cell(x, y, isWall=True)
|
||||
elif ch == "S":
|
||||
if startCell is not None:
|
||||
raise ValueError("Multiple start cells found")
|
||||
cell = Cell(x, y, isWall=False, isStart=True)
|
||||
startCell = cell
|
||||
elif ch == "E":
|
||||
if exitCell is not None:
|
||||
raise ValueError("Multiple exit cells found")
|
||||
cell = Cell(x, y, isWall=False, isExit=True)
|
||||
exitCell = cell
|
||||
elif ch in (" ", "."):
|
||||
cell = Cell(x, y, isWall=False)
|
||||
elif ch.isdigit():
|
||||
cell = Cell(x, y, isWall=False, weight=max(1, int(ch)))
|
||||
else:
|
||||
raise ValueError(f"Unsupported symbol '{ch}' at ({x}, {y})")
|
||||
row.append(cell)
|
||||
cells.append(row)
|
||||
|
||||
if startCell is None:
|
||||
raise ValueError("Start cell 'S' not found")
|
||||
if exitCell is None:
|
||||
raise ValueError("Exit cell 'E' not found")
|
||||
|
||||
return Maze(cells, width, height, startCell, exitCell)
|
||||
|
|
@ -1,11 +0,0 @@
|
|||
from abc import ABC, abstractmethod
|
||||
|
||||
|
||||
class Command(ABC):
|
||||
@abstractmethod
|
||||
def execute(self):
|
||||
raise NotImplementedError
|
||||
|
||||
@abstractmethod
|
||||
def undo(self):
|
||||
raise NotImplementedError
|
||||
|
|
@ -1,37 +0,0 @@
|
|||
from commands.command import Command
|
||||
|
||||
|
||||
class MoveCommand(Command):
|
||||
DIRECTION_TO_DELTA = {
|
||||
"W": (0, -1),
|
||||
"A": (-1, 0),
|
||||
"S": (0, 1),
|
||||
"D": (1, 0),
|
||||
}
|
||||
|
||||
def __init__(self, player, maze, direction):
|
||||
self.player = player
|
||||
self.maze = maze
|
||||
self.direction = direction.upper()
|
||||
self.previousCell = None
|
||||
|
||||
def execute(self):
|
||||
if self.direction not in self.DIRECTION_TO_DELTA:
|
||||
return False
|
||||
|
||||
dx, dy = self.DIRECTION_TO_DELTA[self.direction]
|
||||
current = self.player.currentCell
|
||||
new_cell = self.maze.getCell(current.x + dx, current.y + dy)
|
||||
|
||||
if new_cell is None or not new_cell.isPassable():
|
||||
return False
|
||||
|
||||
self.previousCell = current
|
||||
self.player.setCell(new_cell)
|
||||
return True
|
||||
|
||||
def undo(self):
|
||||
if self.previousCell is None:
|
||||
return False
|
||||
self.player.setCell(self.previousCell)
|
||||
return True
|
||||
|
|
@ -1,30 +0,0 @@
|
|||
from commands.move_command import MoveCommand
|
||||
|
||||
|
||||
class GameController:
|
||||
def __init__(self, maze, player, view):
|
||||
self.maze = maze
|
||||
self.player = player
|
||||
self.view = view
|
||||
self.history = []
|
||||
|
||||
def move(self, direction):
|
||||
command = MoveCommand(self.player, self.maze, direction)
|
||||
if command.execute():
|
||||
self.history.append(command)
|
||||
self.view.update({"type": "move", "direction": direction})
|
||||
self.view.render(self.maze, player_position=self.player.currentCell)
|
||||
return True
|
||||
print("Cannot move there")
|
||||
return False
|
||||
|
||||
def undo(self):
|
||||
if not self.history:
|
||||
print("Nothing to undo")
|
||||
return False
|
||||
command = self.history.pop()
|
||||
if command.undo():
|
||||
self.view.update({"type": "undo"})
|
||||
self.view.render(self.maze, player_position=self.player.currentCell)
|
||||
return True
|
||||
return False
|
||||
|
|
@ -1,26 +0,0 @@
|
|||
from dataclasses import dataclass
|
||||
|
||||
|
||||
@dataclass
|
||||
class Cell:
|
||||
x: int
|
||||
y: int
|
||||
isWall: bool = False
|
||||
isStart: bool = False
|
||||
isExit: bool = False
|
||||
weight: int = 1
|
||||
|
||||
def isPassable(self):
|
||||
return not self.isWall
|
||||
|
||||
def __repr__(self):
|
||||
parts = [f"Cell({self.x}, {self.y}"]
|
||||
if self.isWall:
|
||||
parts.append("WALL")
|
||||
if self.isStart:
|
||||
parts.append("START")
|
||||
if self.isExit:
|
||||
parts.append("EXIT")
|
||||
if self.weight != 1:
|
||||
parts.append(f"w={self.weight}")
|
||||
return ", ".join(parts) + ")"
|
||||
|
|
@ -1,49 +0,0 @@
|
|||
class Maze:
|
||||
def __init__(self, cells, width, height, startCell=None, exitCell=None):
|
||||
self.cells = cells
|
||||
self.width = width
|
||||
self.height = height
|
||||
self.startCell = startCell
|
||||
self.exitCell = exitCell
|
||||
|
||||
def getCell(self, x, y):
|
||||
if 0 <= x < self.width and 0 <= y < self.height:
|
||||
return self.cells[y][x]
|
||||
return None
|
||||
|
||||
def getNeighbors(self, cell):
|
||||
neighbors = []
|
||||
for dx, dy in ((0, -1), (0, 1), (-1, 0), (1, 0)):
|
||||
nx, ny = cell.x + dx, cell.y + dy
|
||||
neighbor = self.getCell(nx, ny)
|
||||
if neighbor is not None and neighbor.isPassable():
|
||||
neighbors.append(neighbor)
|
||||
return neighbors
|
||||
|
||||
def render_lines(self, player_position=None, path=None):
|
||||
path_set = {(c.x, c.y) for c in path} if path else set()
|
||||
player_pos = None if player_position is None else (player_position.x, player_position.y)
|
||||
lines = []
|
||||
for y in range(self.height):
|
||||
row = []
|
||||
for x in range(self.width):
|
||||
cell = self.cells[y][x]
|
||||
if player_pos == (x, y):
|
||||
row.append("P")
|
||||
elif cell.isStart:
|
||||
row.append("S")
|
||||
elif cell.isExit:
|
||||
row.append("E")
|
||||
elif cell.isWall:
|
||||
row.append("#")
|
||||
elif (x, y) in path_set:
|
||||
row.append("*")
|
||||
elif cell.weight > 1:
|
||||
row.append(str(cell.weight))
|
||||
else:
|
||||
row.append(" ")
|
||||
lines.append("".join(row))
|
||||
return lines
|
||||
|
||||
def render(self, player_position=None, path=None):
|
||||
return "\n".join(self.render_lines(player_position=player_position, path=path))
|
||||
|
|
@ -1,6 +0,0 @@
|
|||
class Player:
|
||||
def __init__(self, currentCell):
|
||||
self.currentCell = currentCell
|
||||
|
||||
def setCell(self, cell):
|
||||
self.currentCell = cell
|
||||
|
|
@ -1,11 +0,0 @@
|
|||
from dataclasses import dataclass, field
|
||||
|
||||
|
||||
@dataclass
|
||||
class SearchStats:
|
||||
timeMs: float
|
||||
visitedCells: int
|
||||
pathLength: int
|
||||
path: list = field(default_factory=list)
|
||||
found: bool = False
|
||||
algorithm: str = ""
|
||||
|
|
@ -1 +0,0 @@
|
|||
Place report files and experiment outputs here.
|
||||
|
|
@ -1,249 +0,0 @@
|
|||
# Отчёт по работе «Поиск выхода из лабиринта»
|
||||
|
||||
## 1. Цель работы
|
||||
Разработать гибкую программу для загрузки лабиринта из файла, поиска пути от старта до выхода с возможностью выбора алгоритма, визуализации процесса и экспериментального сравнения алгоритмов. В работе использованы паттерны проектирования, чтобы отделить логику представления лабиринта, его загрузки, поиска пути и вывода результатов.
|
||||
|
||||
## 2. Описание задачи
|
||||
Лабиринт задаётся в текстовом файле символами:
|
||||
- `#` — стена;
|
||||
- пробел — проход;
|
||||
- `S` — старт;
|
||||
- `E` — выход.
|
||||
|
||||
Программа должна:
|
||||
- загружать лабиринт;
|
||||
- строить его внутреннюю модель;
|
||||
- искать путь разными алгоритмами;
|
||||
- собирать статистику поиска;
|
||||
- визуализировать результат в консоли;
|
||||
- сравнивать стратегии на разных типах лабиринтов.
|
||||
|
||||
## 3. Выбранные паттерны проектирования
|
||||
|
||||
### 3.1 Builder
|
||||
Паттерн Builder используется для загрузки лабиринта из файла. Он скрывает детали парсинга и валидации, а клиент получает готовый объект `Maze`.
|
||||
|
||||
Преимущества:
|
||||
- легко добавить новый формат загрузки;
|
||||
- клиентский код не зависит от формата файла;
|
||||
- создание лабиринта можно расширять без переписывания остальной программы.
|
||||
|
||||
### 3.2 Strategy
|
||||
Паттерн Strategy используется для выбора алгоритма поиска пути. В программе реализованы `BFS`, `DFS`, `A*`, а при необходимости можно добавить Дейкстру или любую другую стратегию.
|
||||
|
||||
Преимущества:
|
||||
- алгоритм можно менять во время выполнения;
|
||||
- код оркестратора не зависит от конкретного метода поиска;
|
||||
- новые алгоритмы добавляются без изменения существующего кода.
|
||||
|
||||
### 3.3 Observer
|
||||
Паттерн Observer используется для обновления консольного интерфейса при изменении состояния программы: загрузка лабиринта, поиск пути, движение игрока.
|
||||
|
||||
Преимущества:
|
||||
- вывод отделён от логики;
|
||||
- можно заменить консольный интерфейс на графический без изменения поискового кода;
|
||||
- упрощается расширение визуализации.
|
||||
|
||||
### 3.4 Command
|
||||
Паттерн Command используется для пошагового перемещения игрока и отмены последнего хода.
|
||||
|
||||
Преимущества:
|
||||
- каждое действие оформляется как отдельный объект;
|
||||
- легко реализовать undo;
|
||||
- история ходов хранится отдельно от логики перемещения.
|
||||
|
||||
## 4. Диаграмма классов
|
||||
Ниже приведена упрощённая диаграмма классов в формате Mermaid:
|
||||
|
||||
```mermaid
|
||||
classDiagram
|
||||
class Cell {
|
||||
+int x
|
||||
+int y
|
||||
+bool isWall
|
||||
+bool isStart
|
||||
+bool isExit
|
||||
+isPassable()
|
||||
}
|
||||
|
||||
class Maze {
|
||||
+cells
|
||||
+width
|
||||
+height
|
||||
+startCell
|
||||
+exitCell
|
||||
+getCell(x, y)
|
||||
+getNeighbors(cell)
|
||||
}
|
||||
|
||||
class MazeBuilder {
|
||||
<<interface>>
|
||||
+buildFromFile(filename)
|
||||
}
|
||||
|
||||
class TextFileMazeBuilder {
|
||||
+buildFromFile(filename)
|
||||
}
|
||||
|
||||
class PathFindingStrategy {
|
||||
<<interface>>
|
||||
+findPath(maze, start, exitCell)
|
||||
}
|
||||
|
||||
class BFSStrategy {
|
||||
+findPath(maze, start, exitCell)
|
||||
}
|
||||
|
||||
class DFSStrategy {
|
||||
+findPath(maze, start, exitCell)
|
||||
}
|
||||
|
||||
class AStarStrategy {
|
||||
+findPath(maze, start, exitCell)
|
||||
}
|
||||
|
||||
class SearchStats {
|
||||
+timeMs
|
||||
+visitedCells
|
||||
+pathLength
|
||||
+path
|
||||
}
|
||||
|
||||
class MazeSolver {
|
||||
+maze
|
||||
+strategy
|
||||
+setStrategy(strategy)
|
||||
+solve()
|
||||
}
|
||||
|
||||
class Observer {
|
||||
<<interface>>
|
||||
+update(event)
|
||||
}
|
||||
|
||||
class ConsoleView {
|
||||
+update(event)
|
||||
+render(maze, player_position, path)
|
||||
}
|
||||
|
||||
class Command {
|
||||
<<interface>>
|
||||
+execute()
|
||||
+undo()
|
||||
}
|
||||
|
||||
class MoveCommand {
|
||||
+execute()
|
||||
+undo()
|
||||
}
|
||||
|
||||
class Player {
|
||||
+currentCell
|
||||
+setCell(cell)
|
||||
}
|
||||
|
||||
Maze <|-- TextFileMazeBuilder : creates
|
||||
MazeBuilder <|.. TextFileMazeBuilder
|
||||
PathFindingStrategy <|.. BFSStrategy
|
||||
PathFindingStrategy <|.. DFSStrategy
|
||||
PathFindingStrategy <|.. AStarStrategy
|
||||
MazeSolver --> Maze
|
||||
MazeSolver --> PathFindingStrategy
|
||||
MazeSolver --> SearchStats
|
||||
Observer <|.. ConsoleView
|
||||
Command <|.. MoveCommand
|
||||
MoveCommand --> Player
|
||||
MoveCommand --> Maze
|
||||
ConsoleView --> Maze
|
||||
Maze --> Cell
|
||||
```
|
||||
|
||||
## 5. Ключевые классы и их роль
|
||||
|
||||
### Cell
|
||||
Хранит координаты клетки и её тип. Позволяет быстро проверять, является ли клетка проходимой.
|
||||
|
||||
### Maze
|
||||
Содержит двумерную карту клеток, размер лабиринта, а также ссылки на старт и выход. Даёт доступ к соседним клеткам по четырём направлениям.
|
||||
|
||||
### TextFileMazeBuilder
|
||||
Читает текстовый файл, создаёт объекты `Cell`, определяет старт и выход, затем возвращает готовый `Maze`.
|
||||
|
||||
### BFSStrategy
|
||||
Ищет кратчайший путь по числу шагов. Подходит для случая, когда все переходы одинаковой стоимости.
|
||||
|
||||
### DFSStrategy
|
||||
Быстро исследует пространство, но не гарантирует кратчайший путь. Полезен как сравнительный алгоритм.
|
||||
|
||||
### AStarStrategy
|
||||
Использует эвристику Манхэттенского расстояния. Обычно посещает меньше клеток, чем BFS, если эвристика удачно направляет поиск к цели.
|
||||
|
||||
### MazeSolver
|
||||
Оркестратор, который хранит лабиринт и текущую стратегию. Вызывает поиск, измеряет время и собирает статистику.
|
||||
|
||||
### SearchStats
|
||||
Содержит итог поиска: время выполнения, количество посещённых клеток и длину пути.
|
||||
|
||||
### ConsoleView
|
||||
Реализует наблюдателя и умеет выводить лабиринт и найденный путь в консоль.
|
||||
|
||||
### MoveCommand
|
||||
Оформляет ход игрока как объект-команду. Поддерживает отмену последнего перемещения.
|
||||
|
||||
## 6. Экспериментальная часть
|
||||
|
||||
### 6.1 Подготовка тестовых лабиринтов
|
||||
Для сравнения стратегий использовались следующие типы лабиринтов:
|
||||
- маленький 10×10 с простым путём;
|
||||
- средний 50×50 с тупиками;
|
||||
- большой 100×100 со сложной структурой;
|
||||
- пустой лабиринт без стен;
|
||||
- лабиринт без выхода.
|
||||
|
||||
### 6.2 Методика измерений
|
||||
Для каждой стратегии и каждого лабиринта поиск запускался несколько раз, после чего вычислялись средние значения:
|
||||
- время поиска в миллисекундах;
|
||||
- количество посещённых клеток;
|
||||
- длина найденного пути.
|
||||
|
||||
Результаты сохранялись в CSV-файл в двух вариантах:
|
||||
- сырой набор измерений;
|
||||
- усреднённая таблица.
|
||||
|
||||
## 7. Анализ эффективности
|
||||
|
||||
### BFS
|
||||
BFS гарантирует кратчайший путь по числу шагов, если все переходы имеют одинаковую стоимость. На простых и пустых лабиринтах работает стабильно и предсказуемо. Минус — может посещать много клеток, особенно на больших лабиринтах.
|
||||
|
||||
### DFS
|
||||
DFS может быстро найти какой-то путь, но он не обязательно будет кратчайшим. На сложных лабиринтах иногда работает быстро, но на других может уйти далеко от цели и пройти лишние области.
|
||||
|
||||
### A*
|
||||
A* использует эвристику и обычно показывает хороший баланс между скоростью и качеством пути. На больших и запутанных лабиринтах часто посещает меньше клеток, чем BFS, потому что поиск направлен в сторону выхода.
|
||||
|
||||
### Лабиринт без пути
|
||||
Если пути нет, все алгоритмы вынуждены исследовать доступную область. В этом случае длина пути равна 0, а различия между алгоритмами проявляются в количестве просмотренных клеток и времени выполнения.
|
||||
|
||||
### Вывод по выбору алгоритма
|
||||
- BFS стоит выбирать, когда нужен гарантированно кратчайший путь и веса переходов одинаковы.
|
||||
- DFS полезен как простой и быстрый по реализации вариант, но без гарантии оптимальности.
|
||||
- A* подходит для практических задач, где нужно ускорить поиск и сократить число посещённых клеток.
|
||||
- При взвешенных переходах лучше использовать Дейкстру или взвешенный A*.
|
||||
|
||||
## 8. Роль ООП и паттернов
|
||||
ООП и паттерны сделали код более гибким и расширяемым. Благодаря этому:
|
||||
- можно заменить алгоритм поиска без переписывания логики программы;
|
||||
- можно добавить новый формат загрузки лабиринта;
|
||||
- можно поменять способ визуализации;
|
||||
- можно расширить управление игроком и добавить отмену действий.
|
||||
|
||||
Без паттернов пришлось бы связывать загрузку, поиск, отображение и управление в один большой блок кода. Это усложнило бы отладку и дальнейшие изменения.
|
||||
|
||||
## 9. Вывод
|
||||
В ходе работы была создана расширяемая программа для поиска пути в лабиринте. Использование паттернов Builder, Strategy, Observer и Command позволило разделить обязанности между классами, упростить поддержку кода и сделать архитектуру удобной для дальнейшего развития. Эксперименты показали, что выбор алгоритма сильно зависит от типа лабиринта: BFS даёт кратчайший путь, DFS иногда быстрее в реализации, а A* чаще всего наиболее практичен на больших картах.
|
||||
|
||||
## 10. Приложения
|
||||
- Листинги ключевых классов.
|
||||
- CSV-файлы с результатами экспериментов.
|
||||
- Графики сравнений.
|
||||
- Файлы с тестовыми лабиринтами.
|
||||
|
|
@ -1,225 +0,0 @@
|
|||
from pathlib import Path
|
||||
from statistics import mean
|
||||
import csv
|
||||
import random
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
from core.cell import Cell
|
||||
from core.maze import Maze
|
||||
from solver.maze_solver import MazeSolver
|
||||
from strategies.astar_strategy import AStarStrategy
|
||||
from strategies.bfs_strategy import BFSStrategy
|
||||
from strategies.dfs_strategy import DFSStrategy
|
||||
from strategies.dijkstra_strategy import DijkstraStrategy
|
||||
|
||||
|
||||
BASE_DIR = Path(__file__).resolve().parent
|
||||
OUT_DIR = BASE_DIR / "experiment_results"
|
||||
|
||||
|
||||
def build_maze_from_symbols(lines):
|
||||
height = len(lines)
|
||||
width = max(len(line) for line in lines)
|
||||
cells = []
|
||||
start = None
|
||||
exit_cell = None
|
||||
for y, line in enumerate(lines):
|
||||
row = []
|
||||
for x in range(width):
|
||||
ch = line[x] if x < len(line) else "#"
|
||||
if ch == "#":
|
||||
cell = Cell(x, y, isWall=True)
|
||||
elif ch == "S":
|
||||
cell = Cell(x, y, isWall=False, isStart=True)
|
||||
start = cell
|
||||
elif ch == "E":
|
||||
cell = Cell(x, y, isWall=False, isExit=True)
|
||||
exit_cell = cell
|
||||
elif ch == " " or ch == ".":
|
||||
cell = Cell(x, y, isWall=False)
|
||||
elif ch.isdigit():
|
||||
cell = Cell(x, y, isWall=False, weight=int(ch))
|
||||
else:
|
||||
raise ValueError(f"Unknown symbol '{ch}' at {x},{y}")
|
||||
row.append(cell)
|
||||
cells.append(row)
|
||||
return Maze(cells, width, height, start, exit_cell)
|
||||
|
||||
|
||||
def generate_empty_maze(width, height):
|
||||
lines = [" " * width for _ in range(height)]
|
||||
lines = [list(row) for row in lines]
|
||||
lines[1][1] = "S"
|
||||
lines[height - 2][width - 2] = "E"
|
||||
return build_maze_from_symbols(["".join(row) for row in lines])
|
||||
|
||||
|
||||
def generate_simple_maze(width, height):
|
||||
grid = [["#" for _ in range(width)] for _ in range(height)]
|
||||
for x in range(1, width - 1):
|
||||
grid[1][x] = " "
|
||||
for y in range(1, height - 1):
|
||||
grid[y][width - 2] = " "
|
||||
grid[1][1] = "S"
|
||||
grid[height - 2][width - 2] = "E"
|
||||
return build_maze_from_symbols(["".join(row) for row in grid])
|
||||
|
||||
|
||||
def generate_branching_maze(width, height, seed=42, wall_density=0.30):
|
||||
rng = random.Random(seed)
|
||||
grid = [["#" for _ in range(width)] for _ in range(height)]
|
||||
x, y = 1, 1
|
||||
grid[y][x] = "S"
|
||||
while (x, y) != (width - 2, height - 2):
|
||||
candidates = []
|
||||
for dx, dy in [(1, 0), (0, 1)]:
|
||||
nx, ny = x + dx, y + dy
|
||||
if 1 <= nx < width - 1 and 1 <= ny < height - 1:
|
||||
candidates.append((nx, ny))
|
||||
if not candidates:
|
||||
break
|
||||
x, y = rng.choice(candidates)
|
||||
grid[y][x] = " "
|
||||
grid[height - 2][width - 2] = "E"
|
||||
|
||||
# carve extra corridors and dead ends
|
||||
for yy in range(1, height - 1):
|
||||
for xx in range(1, width - 1):
|
||||
if grid[yy][xx] == "#" and rng.random() > wall_density:
|
||||
grid[yy][xx] = " "
|
||||
grid[1][1] = "S"
|
||||
grid[height - 2][width - 2] = "E"
|
||||
return build_maze_from_symbols(["".join(row) for row in grid])
|
||||
|
||||
|
||||
def generate_no_path_maze(width, height):
|
||||
grid = [[" " for _ in range(width)] for _ in range(height)]
|
||||
for x in range(width):
|
||||
grid[height // 2][x] = "#"
|
||||
grid[1][1] = "S"
|
||||
grid[height - 2][width - 2] = "E"
|
||||
return build_maze_from_symbols(["".join(row) for row in grid])
|
||||
|
||||
|
||||
def generate_weighted_maze(width, height, seed=123):
|
||||
rng = random.Random(seed)
|
||||
grid = [[" " for _ in range(width)] for _ in range(height)]
|
||||
for y in range(height):
|
||||
for x in range(width):
|
||||
r = rng.random()
|
||||
if r < 0.12:
|
||||
grid[y][x] = "#"
|
||||
elif r < 0.25:
|
||||
grid[y][x] = "3"
|
||||
elif r < 0.40:
|
||||
grid[y][x] = "2"
|
||||
else:
|
||||
grid[y][x] = "1"
|
||||
# ensure path-ish
|
||||
for x in range(width):
|
||||
grid[1][x] = "1"
|
||||
for y in range(1, height):
|
||||
grid[y][width - 2] = "1"
|
||||
grid[1][1] = "S"
|
||||
grid[height - 2][width - 2] = "E"
|
||||
return build_maze_from_symbols(["".join(row) for row in grid])
|
||||
|
||||
|
||||
def bench_one_maze(maze_name, maze, strategies, repeats=5):
|
||||
summary_rows = []
|
||||
raw_rows = []
|
||||
for strategy_name, strategy_factory in strategies:
|
||||
times, visiteds, lengths = [], [], []
|
||||
for run in range(1, repeats + 1):
|
||||
solver = MazeSolver(maze)
|
||||
solver.setStrategy(strategy_factory())
|
||||
stats = solver.solve()
|
||||
raw_rows.append([maze_name, strategy_name, run, f"{stats.timeMs:.6f}", stats.visitedCells, stats.pathLength])
|
||||
times.append(stats.timeMs)
|
||||
visiteds.append(stats.visitedCells)
|
||||
lengths.append(stats.pathLength)
|
||||
summary_rows.append([maze_name, strategy_name, f"{mean(times):.6f}", f"{mean(visiteds):.2f}", f"{mean(lengths):.2f}", repeats])
|
||||
return summary_rows, raw_rows
|
||||
|
||||
|
||||
def save_csv(path, rows):
|
||||
with open(path, "w", newline="", encoding="utf-8") as f:
|
||||
csv.writer(f).writerows(rows)
|
||||
|
||||
|
||||
def plot_summary(summary_rows):
|
||||
by_maze = {}
|
||||
for row in summary_rows[1:]:
|
||||
maze_name, strategy, avg_time, avg_visited, avg_len, runs = row
|
||||
by_maze.setdefault(maze_name, []).append((strategy, float(avg_time), float(avg_visited), float(avg_len)))
|
||||
|
||||
for maze_name, items in by_maze.items():
|
||||
items.sort(key=lambda t: t[0])
|
||||
strategies = [i[0] for i in items]
|
||||
x = list(range(len(strategies)))
|
||||
|
||||
plt.figure(figsize=(8, 4))
|
||||
plt.bar(x, [i[1] for i in items])
|
||||
plt.xticks(x, strategies)
|
||||
plt.ylabel("ms")
|
||||
plt.title(f"{maze_name} — avg time")
|
||||
plt.tight_layout()
|
||||
plt.savefig(OUT_DIR / f"{maze_name}_time.png", dpi=150)
|
||||
plt.close()
|
||||
|
||||
plt.figure(figsize=(8, 4))
|
||||
plt.bar(x, [i[2] for i in items])
|
||||
plt.xticks(x, strategies)
|
||||
plt.ylabel("cells")
|
||||
plt.title(f"{maze_name} — visited cells")
|
||||
plt.tight_layout()
|
||||
plt.savefig(OUT_DIR / f"{maze_name}_visited.png", dpi=150)
|
||||
plt.close()
|
||||
|
||||
plt.figure(figsize=(8, 4))
|
||||
plt.bar(x, [i[3] for i in items])
|
||||
plt.xticks(x, strategies)
|
||||
plt.ylabel("cells")
|
||||
plt.title(f"{maze_name} — path length")
|
||||
plt.tight_layout()
|
||||
plt.savefig(OUT_DIR / f"{maze_name}_length.png", dpi=150)
|
||||
plt.close()
|
||||
|
||||
|
||||
def main():
|
||||
OUT_DIR.mkdir(exist_ok=True)
|
||||
|
||||
strategies = [
|
||||
("BFS", BFSStrategy),
|
||||
("DFS", DFSStrategy),
|
||||
("A*", AStarStrategy),
|
||||
("Dijkstra", DijkstraStrategy),
|
||||
]
|
||||
|
||||
mazes = [
|
||||
("small_10x10", generate_simple_maze(10, 10)),
|
||||
("medium_50x50", generate_branching_maze(50, 50)),
|
||||
("large_100x100", generate_branching_maze(100, 100, seed=99, wall_density=0.35)),
|
||||
("empty_30x30", generate_empty_maze(30, 30)),
|
||||
("no_path_30x30", generate_no_path_maze(30, 30)),
|
||||
("weighted_30x30", generate_weighted_maze(30, 30)),
|
||||
]
|
||||
|
||||
summary = [["maze", "strategy", "avg_time_ms", "avg_visited_cells", "avg_path_length", "runs"]]
|
||||
raw = [["maze", "strategy", "run", "time_ms", "visited_cells", "path_length"]]
|
||||
|
||||
for maze_name, maze in mazes:
|
||||
s_rows, r_rows = bench_one_maze(maze_name, maze, strategies, repeats=5)
|
||||
summary.extend(s_rows)
|
||||
raw.extend(r_rows)
|
||||
|
||||
save_csv(OUT_DIR / "summary.csv", summary)
|
||||
save_csv(OUT_DIR / "raw.csv", raw)
|
||||
plot_summary(summary)
|
||||
|
||||
print("Saved to", OUT_DIR.resolve())
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
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|
|
@ -1,121 +0,0 @@
|
|||
maze,strategy,run,time_ms,visited_cells,path_length
|
||||
small_10x10,BFS,1,0.044300,15,15
|
||||
small_10x10,BFS,2,0.022800,15,15
|
||||
small_10x10,BFS,3,0.020400,15,15
|
||||
small_10x10,BFS,4,0.020300,15,15
|
||||
small_10x10,BFS,5,0.018700,15,15
|
||||
small_10x10,DFS,1,0.031200,15,15
|
||||
small_10x10,DFS,2,0.022000,15,15
|
||||
small_10x10,DFS,3,0.021200,15,15
|
||||
small_10x10,DFS,4,0.020800,15,15
|
||||
small_10x10,DFS,5,0.020500,15,15
|
||||
small_10x10,A*,1,0.048900,15,15
|
||||
small_10x10,A*,2,0.034700,15,15
|
||||
small_10x10,A*,3,0.029400,15,15
|
||||
small_10x10,A*,4,0.029100,15,15
|
||||
small_10x10,A*,5,0.029300,15,15
|
||||
small_10x10,Dijkstra,1,0.037900,15,15
|
||||
small_10x10,Dijkstra,2,0.028500,15,15
|
||||
small_10x10,Dijkstra,3,0.026800,15,15
|
||||
small_10x10,Dijkstra,4,0.026400,15,15
|
||||
small_10x10,Dijkstra,5,0.026700,15,15
|
||||
medium_50x50,BFS,1,2.105800,1579,95
|
||||
medium_50x50,BFS,2,1.928700,1579,95
|
||||
medium_50x50,BFS,3,1.969500,1579,95
|
||||
medium_50x50,BFS,4,1.938800,1579,95
|
||||
medium_50x50,BFS,5,1.943600,1579,95
|
||||
medium_50x50,DFS,1,1.927300,1277,647
|
||||
medium_50x50,DFS,2,1.856300,1277,647
|
||||
medium_50x50,DFS,3,1.890100,1277,647
|
||||
medium_50x50,DFS,4,1.868000,1277,647
|
||||
medium_50x50,DFS,5,1.865500,1277,647
|
||||
medium_50x50,A*,1,2.359000,927,95
|
||||
medium_50x50,A*,2,2.193700,927,95
|
||||
medium_50x50,A*,3,2.178400,927,95
|
||||
medium_50x50,A*,4,2.181800,927,95
|
||||
medium_50x50,A*,5,2.174500,927,95
|
||||
medium_50x50,Dijkstra,1,3.534700,1579,95
|
||||
medium_50x50,Dijkstra,2,3.435500,1579,95
|
||||
medium_50x50,Dijkstra,3,3.457600,1579,95
|
||||
medium_50x50,Dijkstra,4,3.417300,1579,95
|
||||
medium_50x50,Dijkstra,5,3.538000,1579,95
|
||||
large_100x100,BFS,1,8.624100,5566,195
|
||||
large_100x100,BFS,2,7.706900,5566,195
|
||||
large_100x100,BFS,3,9.723300,5566,195
|
||||
large_100x100,BFS,4,7.585700,5566,195
|
||||
large_100x100,BFS,5,8.031300,5566,195
|
||||
large_100x100,DFS,1,5.512400,3543,1531
|
||||
large_100x100,DFS,2,5.329300,3543,1531
|
||||
large_100x100,DFS,3,5.223300,3543,1531
|
||||
large_100x100,DFS,4,5.729900,3543,1531
|
||||
large_100x100,DFS,5,5.497400,3543,1531
|
||||
large_100x100,A*,1,2.101500,853,195
|
||||
large_100x100,A*,2,2.264500,853,195
|
||||
large_100x100,A*,3,2.064100,853,195
|
||||
large_100x100,A*,4,2.031700,853,195
|
||||
large_100x100,A*,5,2.046500,853,195
|
||||
large_100x100,Dijkstra,1,25.021300,5571,195
|
||||
large_100x100,Dijkstra,2,13.541100,5571,195
|
||||
large_100x100,Dijkstra,3,12.884100,5571,195
|
||||
large_100x100,Dijkstra,4,13.481800,5571,195
|
||||
large_100x100,Dijkstra,5,12.748000,5571,195
|
||||
empty_30x30,BFS,1,1.234300,896,55
|
||||
empty_30x30,BFS,2,1.163400,896,55
|
||||
empty_30x30,BFS,3,1.145700,896,55
|
||||
empty_30x30,BFS,4,1.177300,896,55
|
||||
empty_30x30,BFS,5,1.175100,896,55
|
||||
empty_30x30,DFS,1,1.338000,842,815
|
||||
empty_30x30,DFS,2,1.296500,842,815
|
||||
empty_30x30,DFS,3,1.296700,842,815
|
||||
empty_30x30,DFS,4,1.280100,842,815
|
||||
empty_30x30,DFS,5,1.290800,842,815
|
||||
empty_30x30,A*,1,2.183400,784,55
|
||||
empty_30x30,A*,2,2.522900,784,55
|
||||
empty_30x30,A*,3,1.985000,784,55
|
||||
empty_30x30,A*,4,1.972100,784,55
|
||||
empty_30x30,A*,5,2.088600,784,55
|
||||
empty_30x30,Dijkstra,1,2.080400,896,55
|
||||
empty_30x30,Dijkstra,2,2.100100,896,55
|
||||
empty_30x30,Dijkstra,3,2.130700,896,55
|
||||
empty_30x30,Dijkstra,4,2.073600,896,55
|
||||
empty_30x30,Dijkstra,5,2.095900,896,55
|
||||
no_path_30x30,BFS,1,0.645900,450,0
|
||||
no_path_30x30,BFS,2,0.566600,450,0
|
||||
no_path_30x30,BFS,3,0.566000,450,0
|
||||
no_path_30x30,BFS,4,0.583500,450,0
|
||||
no_path_30x30,BFS,5,0.568900,450,0
|
||||
no_path_30x30,DFS,1,0.692100,450,0
|
||||
no_path_30x30,DFS,2,0.676900,450,0
|
||||
no_path_30x30,DFS,3,0.703500,450,0
|
||||
no_path_30x30,DFS,4,0.722300,450,0
|
||||
no_path_30x30,DFS,5,0.672000,450,0
|
||||
no_path_30x30,A*,1,1.112700,450,0
|
||||
no_path_30x30,A*,2,1.130000,450,0
|
||||
no_path_30x30,A*,3,1.096100,450,0
|
||||
no_path_30x30,A*,4,1.111400,450,0
|
||||
no_path_30x30,A*,5,1.183500,450,0
|
||||
no_path_30x30,Dijkstra,1,1.023300,450,0
|
||||
no_path_30x30,Dijkstra,2,1.011700,450,0
|
||||
no_path_30x30,Dijkstra,3,1.127200,450,0
|
||||
no_path_30x30,Dijkstra,4,1.110200,450,0
|
||||
no_path_30x30,Dijkstra,5,1.043900,450,0
|
||||
weighted_30x30,BFS,1,1.074700,788,55
|
||||
weighted_30x30,BFS,2,0.997700,788,55
|
||||
weighted_30x30,BFS,3,0.992700,788,55
|
||||
weighted_30x30,BFS,4,1.010800,788,55
|
||||
weighted_30x30,BFS,5,1.035000,788,55
|
||||
weighted_30x30,DFS,1,1.130200,693,479
|
||||
weighted_30x30,DFS,2,1.057400,693,479
|
||||
weighted_30x30,DFS,3,1.049900,693,479
|
||||
weighted_30x30,DFS,4,1.051600,693,479
|
||||
weighted_30x30,DFS,5,1.059100,693,479
|
||||
weighted_30x30,A*,1,0.402200,126,55
|
||||
weighted_30x30,A*,2,0.384100,126,55
|
||||
weighted_30x30,A*,3,0.360000,126,55
|
||||
weighted_30x30,A*,4,0.360700,126,55
|
||||
weighted_30x30,A*,5,0.353500,126,55
|
||||
weighted_30x30,Dijkstra,1,1.834900,781,55
|
||||
weighted_30x30,Dijkstra,2,1.759000,781,55
|
||||
weighted_30x30,Dijkstra,3,1.786300,781,55
|
||||
weighted_30x30,Dijkstra,4,1.740500,781,55
|
||||
weighted_30x30,Dijkstra,5,1.807100,781,55
|
||||
|
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|
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|
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|
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|
|
@ -1,25 +0,0 @@
|
|||
maze,strategy,avg_time_ms,avg_visited_cells,avg_path_length,runs
|
||||
small_10x10,BFS,0.025300,15.00,15.00,5
|
||||
small_10x10,DFS,0.023140,15.00,15.00,5
|
||||
small_10x10,A*,0.034280,15.00,15.00,5
|
||||
small_10x10,Dijkstra,0.029260,15.00,15.00,5
|
||||
medium_50x50,BFS,1.977280,1579.00,95.00,5
|
||||
medium_50x50,DFS,1.881440,1277.00,647.00,5
|
||||
medium_50x50,A*,2.217480,927.00,95.00,5
|
||||
medium_50x50,Dijkstra,3.476620,1579.00,95.00,5
|
||||
large_100x100,BFS,8.334260,5566.00,195.00,5
|
||||
large_100x100,DFS,5.458460,3543.00,1531.00,5
|
||||
large_100x100,A*,2.101660,853.00,195.00,5
|
||||
large_100x100,Dijkstra,15.535260,5571.00,195.00,5
|
||||
empty_30x30,BFS,1.179160,896.00,55.00,5
|
||||
empty_30x30,DFS,1.300420,842.00,815.00,5
|
||||
empty_30x30,A*,2.150400,784.00,55.00,5
|
||||
empty_30x30,Dijkstra,2.096140,896.00,55.00,5
|
||||
no_path_30x30,BFS,0.586180,450.00,0.00,5
|
||||
no_path_30x30,DFS,0.693360,450.00,0.00,5
|
||||
no_path_30x30,A*,1.126740,450.00,0.00,5
|
||||
no_path_30x30,Dijkstra,1.063260,450.00,0.00,5
|
||||
weighted_30x30,BFS,1.022180,788.00,55.00,5
|
||||
weighted_30x30,DFS,1.069640,693.00,479.00,5
|
||||
weighted_30x30,A*,0.372100,126.00,55.00,5
|
||||
weighted_30x30,Dijkstra,1.785560,781.00,55.00,5
|
||||
|
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|
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|
Before Width: | Height: | Size: 22 KiB |
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|
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|
|
@ -1,59 +0,0 @@
|
|||
from builders.text_file_maze_builder import TextFileMazeBuilder
|
||||
from core.player import Player
|
||||
from observer.console_view import ConsoleView
|
||||
from solver.maze_solver import MazeSolver
|
||||
from strategies.astar_strategy import AStarStrategy
|
||||
from strategies.bfs_strategy import BFSStrategy
|
||||
from strategies.dfs_strategy import DFSStrategy
|
||||
from controller.game_controller import GameController
|
||||
|
||||
|
||||
from pathlib import Path
|
||||
|
||||
BASE_DIR = Path(__file__).resolve().parent
|
||||
|
||||
|
||||
def run_demo():
|
||||
builder = TextFileMazeBuilder()
|
||||
maze = builder.buildFromFile(str(BASE_DIR / "mazes" / "maze_small.txt"))
|
||||
|
||||
view = ConsoleView()
|
||||
view.update({"type": "maze_loaded", "message": "Maze loaded"})
|
||||
view.render(maze)
|
||||
|
||||
solver = MazeSolver(maze)
|
||||
solver.addObserver(view)
|
||||
|
||||
for strategy in (BFSStrategy(), DFSStrategy(), AStarStrategy()):
|
||||
solver.setStrategy(strategy)
|
||||
stats = solver.solve()
|
||||
|
||||
print()
|
||||
print(f"=== {strategy.name} ===")
|
||||
print(f"Time: {stats.timeMs:.3f} ms")
|
||||
print(f"Visited cells: {stats.visitedCells}")
|
||||
print(f"Path length: {stats.pathLength}")
|
||||
print(f"Path found: {'yes' if stats.found else 'no'}")
|
||||
|
||||
view.render(maze, path=stats.path)
|
||||
|
||||
player = Player(maze.startCell)
|
||||
controller = GameController(maze, player, view)
|
||||
|
||||
print("Manual mode: W/A/S/D move, Z undo, Q quit")
|
||||
view.render(maze, player_position=player.currentCell)
|
||||
|
||||
while True:
|
||||
cmd = input("Command: ").strip().upper()
|
||||
if cmd == "Q":
|
||||
break
|
||||
if cmd == "Z":
|
||||
controller.undo()
|
||||
elif cmd in {"W", "A", "S", "D"}:
|
||||
controller.move(cmd)
|
||||
else:
|
||||
print("Unknown command")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
run_demo()
|
||||
|
|
@ -1,9 +0,0 @@
|
|||
S
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
E
|
||||
|
|
@ -1,11 +0,0 @@
|
|||
####################################################################################################
|
||||
#S # # # # # # # # # # # # # # # E#
|
||||
# # ### ### # ###### # ### # ## # #### # ####### # #### # # ### ## # ## # # ## # ## # ##### ### ##
|
||||
# # # # # # # # # # # # # # # # # # # # # # # # # # #
|
||||
# ##### # ######## # ### # ## # #### # ####### ## ### # # #### ####### ## ####### ####### # ### ##
|
||||
# # # # # # # # # # # # # # # # # # # # #
|
||||
### # # ###### # ########### ########### ### ####### # ####### ### # # ###### # ### ### # ### ####
|
||||
# # # # # # # # # # # # # # # # # # # # # #
|
||||
# ### ###### # ##### # ### # ####### # ### ### ## # ###### # ### # ### ###### # ### # ### ### ## #
|
||||
# # # # # # # # #
|
||||
####################################################################################################
|
||||
|
|
@ -1,11 +0,0 @@
|
|||
##################################################
|
||||
#S # # # # # # E#
|
||||
# # ### ### # ###### # ### # ## # #### # ####### ##
|
||||
# # # # # # # # # # # # # #
|
||||
# ##### # ######## # ### # ## # #### # ####### ## #
|
||||
# # # # # # # # # #
|
||||
### # # ###### # ########### ########### ### ######
|
||||
# # # # # # # # # # #
|
||||
# ### ###### # ##### # ### # ####### # ### ### ## #
|
||||
# # # # #
|
||||
##################################################
|
||||
|
|
@ -1,9 +0,0 @@
|
|||
##########
|
||||
#S #
|
||||
# ###### #
|
||||
# # #
|
||||
##########
|
||||
# #E#
|
||||
# ###### #
|
||||
# #
|
||||
##########
|
||||
|
|
@ -1,7 +0,0 @@
|
|||
##########
|
||||
#S #E#
|
||||
# ## # # ##
|
||||
# # #
|
||||
# #### # #
|
||||
# # #
|
||||
##########
|
||||
|
|
@ -1,10 +0,0 @@
|
|||
1111111111111111111111111111
|
||||
1S11111111111111111111111111
|
||||
1111111111111111111111111111
|
||||
1111111111111111111111111111
|
||||
1111111111111222222222222111
|
||||
1111111111111222222222222111
|
||||
1111111111111333333333333111
|
||||
1111111111111333333333333111
|
||||
111111111111111111111111111E
|
||||
1111111111111111111111111111
|
||||
|
|
@ -1,26 +0,0 @@
|
|||
import os
|
||||
from observer.observer import Observer
|
||||
|
||||
|
||||
class ConsoleView(Observer):
|
||||
def update(self, event):
|
||||
if isinstance(event, str):
|
||||
print(f"[EVENT] {event}")
|
||||
elif isinstance(event, dict):
|
||||
event_type = event.get("type", "unknown")
|
||||
if event_type == "search_finished":
|
||||
stats = event.get("stats")
|
||||
print(f"[EVENT] search finished: {stats}")
|
||||
else:
|
||||
print(f"[EVENT] {event_type}: {event}")
|
||||
else:
|
||||
print("[EVENT] unknown")
|
||||
|
||||
def clear(self):
|
||||
os.system("cls" if os.name == "nt" else "clear")
|
||||
|
||||
def render(self, maze, player_position=None, path=None, clear_screen=False):
|
||||
if clear_screen:
|
||||
self.clear()
|
||||
print(maze.render(player_position=player_position, path=path))
|
||||
print()
|
||||
|
|
@ -1,7 +0,0 @@
|
|||
from abc import ABC, abstractmethod
|
||||
|
||||
|
||||
class Observer(ABC):
|
||||
@abstractmethod
|
||||
def update(self, event):
|
||||
raise NotImplementedError
|
||||
|
|
@ -1 +0,0 @@
|
|||
matplotlib
|
||||
|
|
@ -1,50 +0,0 @@
|
|||
import time
|
||||
from core.search_stats import SearchStats
|
||||
|
||||
|
||||
class MazeSolver:
|
||||
def __init__(self, maze, strategy=None):
|
||||
self.maze = maze
|
||||
self.strategy = strategy
|
||||
self.observers = []
|
||||
|
||||
def setStrategy(self, strategy):
|
||||
self.strategy = strategy
|
||||
|
||||
def addObserver(self, observer):
|
||||
if observer not in self.observers:
|
||||
self.observers.append(observer)
|
||||
|
||||
def removeObserver(self, observer):
|
||||
if observer in self.observers:
|
||||
self.observers.remove(observer)
|
||||
|
||||
def notify(self, event):
|
||||
for observer in self.observers:
|
||||
observer.update(event)
|
||||
|
||||
def solve(self):
|
||||
if self.strategy is None:
|
||||
raise ValueError("Strategy is not set")
|
||||
self.notify({"type": "search_started", "strategy": self.strategy.name})
|
||||
|
||||
start_time = time.perf_counter()
|
||||
path = self.strategy.findPath(self.maze, self.maze.startCell, self.maze.exitCell)
|
||||
end_time = time.perf_counter()
|
||||
|
||||
stats = SearchStats(
|
||||
timeMs=(end_time - start_time) * 1000.0,
|
||||
visitedCells=getattr(self.strategy, "visitedCount", 0),
|
||||
pathLength=len(path),
|
||||
path=path,
|
||||
found=bool(path),
|
||||
algorithm=getattr(self.strategy, "name", "")
|
||||
)
|
||||
|
||||
if stats.found:
|
||||
self.notify({"type": "path_found", "strategy": stats.algorithm, "length": stats.pathLength})
|
||||
else:
|
||||
self.notify({"type": "path_not_found", "strategy": stats.algorithm})
|
||||
|
||||
self.notify({"type": "search_finished", "stats": stats})
|
||||
return stats
|
||||
|
|
@ -1,45 +0,0 @@
|
|||
import heapq
|
||||
from strategies.pathfinding_strategy import PathFindingStrategy
|
||||
|
||||
|
||||
class AStarStrategy(PathFindingStrategy):
|
||||
name = "A*"
|
||||
|
||||
def heuristic(self, cell, exitCell):
|
||||
return abs(cell.x - exitCell.x) + abs(cell.y - exitCell.y)
|
||||
|
||||
def findPath(self, maze, start, exitCell):
|
||||
self.visitedCount = 0
|
||||
if start is None or exitCell is None:
|
||||
return []
|
||||
|
||||
open_set = []
|
||||
heapq.heappush(open_set, (0, 0, start.x, start.y, start))
|
||||
parent = {}
|
||||
g_score = {(start.x, start.y): 0}
|
||||
closed = set()
|
||||
|
||||
while open_set:
|
||||
f_score, current_g, _, _, current = heapq.heappop(open_set)
|
||||
pos = (current.x, current.y)
|
||||
|
||||
if pos in closed:
|
||||
continue
|
||||
|
||||
closed.add(pos)
|
||||
self.visitedCount += 1
|
||||
|
||||
if current.x == exitCell.x and current.y == exitCell.y:
|
||||
return self._restore_path(parent, start, exitCell)
|
||||
|
||||
for neighbor in maze.getNeighbors(current):
|
||||
npos = (neighbor.x, neighbor.y)
|
||||
tentative_g = current_g + getattr(neighbor, "weight", 1)
|
||||
|
||||
if tentative_g < g_score.get(npos, float("inf")):
|
||||
g_score[npos] = tentative_g
|
||||
parent[npos] = current
|
||||
new_f = tentative_g + self.heuristic(neighbor, exitCell)
|
||||
heapq.heappush(open_set, (new_f, tentative_g, neighbor.x, neighbor.y, neighbor))
|
||||
|
||||
return []
|
||||
|
|
@ -1,31 +0,0 @@
|
|||
from collections import deque
|
||||
from strategies.pathfinding_strategy import PathFindingStrategy
|
||||
|
||||
|
||||
class BFSStrategy(PathFindingStrategy):
|
||||
name = "BFS"
|
||||
|
||||
def findPath(self, maze, start, exitCell):
|
||||
self.visitedCount = 0
|
||||
if start is None or exitCell is None:
|
||||
return []
|
||||
|
||||
queue = deque([start])
|
||||
visited = {(start.x, start.y)}
|
||||
parent = {}
|
||||
|
||||
while queue:
|
||||
current = queue.popleft()
|
||||
self.visitedCount += 1
|
||||
|
||||
if current.x == exitCell.x and current.y == exitCell.y:
|
||||
return self._restore_path(parent, start, exitCell)
|
||||
|
||||
for neighbor in maze.getNeighbors(current):
|
||||
pos = (neighbor.x, neighbor.y)
|
||||
if pos not in visited:
|
||||
visited.add(pos)
|
||||
parent[pos] = current
|
||||
queue.append(neighbor)
|
||||
|
||||
return []
|
||||
|
|
@ -1,35 +0,0 @@
|
|||
from strategies.pathfinding_strategy import PathFindingStrategy
|
||||
|
||||
|
||||
class DFSStrategy(PathFindingStrategy):
|
||||
name = "DFS"
|
||||
|
||||
def findPath(self, maze, start, exitCell):
|
||||
self.visitedCount = 0
|
||||
if start is None or exitCell is None:
|
||||
return []
|
||||
|
||||
stack = [start]
|
||||
visited = set()
|
||||
parent = {}
|
||||
|
||||
while stack:
|
||||
current = stack.pop()
|
||||
pos = (current.x, current.y)
|
||||
if pos in visited:
|
||||
continue
|
||||
|
||||
visited.add(pos)
|
||||
self.visitedCount += 1
|
||||
|
||||
if current.x == exitCell.x and current.y == exitCell.y:
|
||||
return self._restore_path(parent, start, exitCell)
|
||||
|
||||
neighbors = maze.getNeighbors(current)
|
||||
for neighbor in reversed(neighbors):
|
||||
npos = (neighbor.x, neighbor.y)
|
||||
if npos not in visited:
|
||||
parent[npos] = current
|
||||
stack.append(neighbor)
|
||||
|
||||
return []
|
||||
|
|
@ -1,41 +0,0 @@
|
|||
import heapq
|
||||
from strategies.pathfinding_strategy import PathFindingStrategy
|
||||
|
||||
|
||||
class DijkstraStrategy(PathFindingStrategy):
|
||||
name = "Dijkstra"
|
||||
|
||||
def findPath(self, maze, start, exitCell):
|
||||
self.visitedCount = 0
|
||||
if start is None or exitCell is None:
|
||||
return []
|
||||
|
||||
pq = [(0, start.x, start.y, start)]
|
||||
dist = {(start.x, start.y): 0}
|
||||
parent = {}
|
||||
closed = set()
|
||||
|
||||
while pq:
|
||||
current_cost, _, _, current = heapq.heappop(pq)
|
||||
pos = (current.x, current.y)
|
||||
|
||||
if pos in closed:
|
||||
continue
|
||||
|
||||
closed.add(pos)
|
||||
self.visitedCount += 1
|
||||
|
||||
if current.x == exitCell.x and current.y == exitCell.y:
|
||||
return self._restore_path(parent, start, exitCell)
|
||||
|
||||
for neighbor in maze.getNeighbors(current):
|
||||
npos = (neighbor.x, neighbor.y)
|
||||
step_cost = getattr(neighbor, "weight", 1)
|
||||
new_cost = current_cost + step_cost
|
||||
|
||||
if new_cost < dist.get(npos, float("inf")):
|
||||
dist[npos] = new_cost
|
||||
parent[npos] = current
|
||||
heapq.heappush(pq, (new_cost, neighbor.x, neighbor.y, neighbor))
|
||||
|
||||
return []
|
||||
|
|
@ -1,30 +0,0 @@
|
|||
from abc import ABC, abstractmethod
|
||||
|
||||
|
||||
class PathFindingStrategy(ABC):
|
||||
name = "Base"
|
||||
|
||||
def __init__(self):
|
||||
self.visitedCount = 0
|
||||
|
||||
@abstractmethod
|
||||
def findPath(self, maze, start, exitCell):
|
||||
raise NotImplementedError
|
||||
|
||||
def _restore_path(self, parent, start, exitCell):
|
||||
if exitCell is None or start is None:
|
||||
return []
|
||||
|
||||
path = []
|
||||
current = exitCell
|
||||
|
||||
while True:
|
||||
path.append(current)
|
||||
if current.x == start.x and current.y == start.y:
|
||||
break
|
||||
current = parent.get((current.x, current.y))
|
||||
if current is None:
|
||||
return []
|
||||
|
||||
path.reverse()
|
||||
return path
|
||||
|
|
@ -1 +0,0 @@
|
|||
|
||||
|
|
@ -1,71 +0,0 @@
|
|||
def create_node(name, phone):
|
||||
return {'name': name, 'phone': phone, 'left': None, 'right': None}
|
||||
|
||||
def bst_insert(root, name, phone):
|
||||
if root is None:
|
||||
return create_node(name, phone)
|
||||
|
||||
if name == root['name']:
|
||||
root['phone'] = phone
|
||||
elif name < root['name']:
|
||||
root['left'] = bst_insert(root['left'], name, phone)
|
||||
else:
|
||||
root['right'] = bst_insert(root['right'], name, phone)
|
||||
return root
|
||||
|
||||
def bst_find(root, name):
|
||||
if root is None:
|
||||
return None
|
||||
if name == root['name']:
|
||||
return root['phone']
|
||||
elif name < root['name']:
|
||||
return bst_find(root['left'], name)
|
||||
else:
|
||||
return bst_find(root['right'], name)
|
||||
|
||||
def _find_min(node):
|
||||
while node['left'] is not None:
|
||||
node = node['left']
|
||||
return node
|
||||
|
||||
def bst_delete(root, name):
|
||||
if root is None:
|
||||
return None
|
||||
|
||||
if name < root['name']:
|
||||
root['left'] = bst_delete(root['left'], name)
|
||||
elif name > root['name']:
|
||||
root['right'] = bst_delete(root['right'], name)
|
||||
else:
|
||||
if root['left'] is None:
|
||||
return root['right']
|
||||
if root['right'] is None:
|
||||
return root['left']
|
||||
min_node = _find_min(root['right'])
|
||||
root['name'] = min_node['name']
|
||||
root['phone'] = min_node['phone']
|
||||
root['right'] = bst_delete(root['right'], min_node['name'])
|
||||
return root
|
||||
|
||||
def bst_list_all(root):
|
||||
result = []
|
||||
def inorder(node):
|
||||
if node is None:
|
||||
return
|
||||
inorder(node['left'])
|
||||
result.append((node['name'], node['phone']))
|
||||
inorder(node['right'])
|
||||
inorder(root)
|
||||
return result
|
||||
|
||||
if __name__ == '__main__':
|
||||
root = None
|
||||
root = bst_insert(root, 'Иван', '123-456')
|
||||
root = bst_insert(root, 'Борис', '789-012')
|
||||
root = bst_insert(root, 'Анна', '345-678')
|
||||
root = bst_insert(root, 'Иван', '111-222')
|
||||
print(bst_list_all(root))
|
||||
print(bst_find(root, 'Иван'))
|
||||
print(bst_find(root, 'Петр'))
|
||||
root = bst_delete(root, 'Борис')
|
||||
print(bst_list_all(root))
|
||||
|
|
@ -1,126 +0,0 @@
|
|||
import random
|
||||
import time
|
||||
import csv
|
||||
import sys
|
||||
sys.setrecursionlimit(20000)
|
||||
|
||||
from linked_list_phonebook import ll_insert, ll_find, ll_delete, ll_list_all
|
||||
from hash_table_phonebook import ht_insert, ht_find, ht_delete, ht_list_all
|
||||
from bst_phonebook import bst_insert, bst_find, bst_delete, bst_list_all
|
||||
|
||||
def generate_records(n, seed=42):
|
||||
random.seed(seed)
|
||||
records = []
|
||||
for i in range(1, n+1):
|
||||
name = f"User_{i:05d}"
|
||||
phone = f"{random.randint(100,999)}-{random.randint(1000,9999)}"
|
||||
records.append((name, phone))
|
||||
return records
|
||||
|
||||
def prepare_datasets(base_records):
|
||||
shuffled = base_records.copy()
|
||||
random.shuffle(shuffled)
|
||||
sorted_records = sorted(base_records, key=lambda x: x[0])
|
||||
return shuffled, sorted_records
|
||||
|
||||
def run_experiment(struct_funcs, records, mode_name, repeats=5):
|
||||
results = []
|
||||
for rep in range(repeats):
|
||||
struct = struct_funcs['create']()
|
||||
|
||||
start = time.perf_counter()
|
||||
for name, phone in records:
|
||||
struct = struct_funcs['insert'](struct, name, phone)
|
||||
end = time.perf_counter()
|
||||
insert_time = end - start
|
||||
|
||||
existing_names = [name for name, _ in records]
|
||||
sample_existing = random.sample(existing_names, 100)
|
||||
nonexistent = [f"NotExist_{i}" for i in range(10)]
|
||||
search_names = sample_existing + nonexistent
|
||||
random.shuffle(search_names)
|
||||
|
||||
start = time.perf_counter()
|
||||
for name in search_names:
|
||||
_ = struct_funcs['find'](struct, name)
|
||||
end = time.perf_counter()
|
||||
find_time = end - start
|
||||
|
||||
to_delete = random.sample(existing_names, 50)
|
||||
start = time.perf_counter()
|
||||
for name in to_delete:
|
||||
struct = struct_funcs['delete'](struct, name)
|
||||
end = time.perf_counter()
|
||||
delete_time = end - start
|
||||
|
||||
results.append({
|
||||
'structure': struct_funcs['name'],
|
||||
'mode': mode_name,
|
||||
'repetition': rep+1,
|
||||
'insert_time': insert_time,
|
||||
'find_time': find_time,
|
||||
'delete_time': delete_time
|
||||
})
|
||||
return results
|
||||
|
||||
def main():
|
||||
N = 10000
|
||||
base_records = generate_records(N)
|
||||
shuffled, sorted_records = prepare_datasets(base_records)
|
||||
|
||||
structures = {
|
||||
'LinkedList': {
|
||||
'name': 'LinkedList',
|
||||
'create': lambda: None,
|
||||
'insert': ll_insert,
|
||||
'find': ll_find,
|
||||
'delete': ll_delete,
|
||||
'list_all': ll_list_all
|
||||
},
|
||||
'HashTable': {
|
||||
'name': 'HashTable',
|
||||
'create': lambda: [None] * 10,
|
||||
'insert': ht_insert,
|
||||
'find': ht_find,
|
||||
'delete': ht_delete,
|
||||
'list_all': ht_list_all
|
||||
},
|
||||
'BST': {
|
||||
'name': 'BST',
|
||||
'create': lambda: None,
|
||||
'insert': bst_insert,
|
||||
'find': bst_find,
|
||||
'delete': bst_delete,
|
||||
'list_all': bst_list_all
|
||||
}
|
||||
}
|
||||
|
||||
all_results = []
|
||||
repeats = 5
|
||||
|
||||
for struct_name, funcs in structures.items():
|
||||
print(f"Testing {struct_name} on random order...")
|
||||
res_random = run_experiment(funcs, shuffled, 'random', repeats)
|
||||
all_results.extend(res_random)
|
||||
|
||||
print(f"Testing {struct_name} on sorted order...")
|
||||
res_sorted = run_experiment(funcs, sorted_records, 'sorted', repeats)
|
||||
all_results.extend(res_sorted)
|
||||
|
||||
with open('experiment_results.csv', 'w', newline='', encoding='utf-8') as f:
|
||||
writer = csv.writer(f)
|
||||
writer.writerow(['Structure', 'Mode', 'Repeat', 'Insert (sec)', 'Search (sec)', 'Delete (sec)'])
|
||||
for r in all_results:
|
||||
writer.writerow([
|
||||
r['structure'],
|
||||
r['mode'],
|
||||
r['repetition'],
|
||||
f"{r['insert_time']:.6f}",
|
||||
f"{r['find_time']:.6f}",
|
||||
f"{r['delete_time']:.6f}"
|
||||
])
|
||||
|
||||
print("Experiment finished. Results saved to experiment_results.csv")
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
|
|
@ -1,31 +0,0 @@
|
|||
Structure,Mode,Repeat,Insert (sec),Search (sec),Delete (sec)
|
||||
LinkedList,random,1,4.432559,0.034196,0.014270
|
||||
LinkedList,random,2,4.999931,0.038043,0.020281
|
||||
LinkedList,random,3,4.771456,0.030191,0.014131
|
||||
LinkedList,random,4,4.707315,0.033500,0.016198
|
||||
LinkedList,random,5,4.721361,0.036586,0.011988
|
||||
LinkedList,sorted,1,4.139028,0.024011,0.010482
|
||||
LinkedList,sorted,2,4.212383,0.024592,0.011765
|
||||
LinkedList,sorted,3,4.674211,0.027756,0.012189
|
||||
LinkedList,sorted,4,4.610210,0.031519,0.012244
|
||||
LinkedList,sorted,5,4.565687,0.029739,0.012747
|
||||
HashTable,random,1,0.659990,0.003889,0.001728
|
||||
HashTable,random,2,0.666055,0.005980,0.002002
|
||||
HashTable,random,3,0.669948,0.004087,0.002176
|
||||
HashTable,random,4,0.661882,0.007439,0.001897
|
||||
HashTable,random,5,0.680420,0.004016,0.001649
|
||||
HashTable,sorted,1,0.648261,0.004277,0.002922
|
||||
HashTable,sorted,2,0.654924,0.004136,0.001793
|
||||
HashTable,sorted,3,0.645509,0.003900,0.002249
|
||||
HashTable,sorted,4,0.637906,0.004056,0.001657
|
||||
HashTable,sorted,5,0.643536,0.003846,0.001741
|
||||
BST,random,1,0.029415,0.000515,0.000183
|
||||
BST,random,2,0.027684,0.000216,0.000142
|
||||
BST,random,3,0.026213,0.000252,0.000159
|
||||
BST,random,4,0.026987,0.000207,0.000135
|
||||
BST,random,5,0.028321,0.000271,0.000183
|
||||
BST,sorted,1,10.293772,0.093178,0.053520
|
||||
BST,sorted,2,10.142204,0.088924,0.049079
|
||||
BST,sorted,3,10.142037,0.078281,0.059416
|
||||
BST,sorted,4,10.139818,0.100162,0.056881
|
||||
BST,sorted,5,10.102982,0.082247,0.051973
|
||||
|
|
|
@ -1,47 +0,0 @@
|
|||
from linked_list_phonebook import ll_insert, ll_find, ll_delete, ll_list_all
|
||||
|
||||
def hash_function(name, table_size):
|
||||
return hash(name) % table_size
|
||||
|
||||
def ht_insert(buckets, name, phone):
|
||||
idx = hash_function(name, len(buckets))
|
||||
head = buckets[idx]
|
||||
new_head = ll_insert(head, name, phone)
|
||||
buckets[idx] = new_head
|
||||
return buckets
|
||||
|
||||
def ht_find(buckets, name):
|
||||
idx = hash_function(name, len(buckets))
|
||||
head = buckets[idx]
|
||||
return ll_find(head, name)
|
||||
|
||||
def ht_delete(buckets, name):
|
||||
idx = hash_function(name, len(buckets))
|
||||
head = buckets[idx]
|
||||
new_head = ll_delete(head, name)
|
||||
buckets[idx] = new_head
|
||||
return buckets
|
||||
|
||||
def ht_list_all(buckets):
|
||||
all_records = []
|
||||
for head in buckets:
|
||||
current = head
|
||||
while current is not None:
|
||||
all_records.append((current['name'], current['phone']))
|
||||
current = current['next']
|
||||
all_records.sort(key=lambda x: x[0])
|
||||
return all_records
|
||||
|
||||
if __name__ == '__main__':
|
||||
SIZE = 5
|
||||
buckets = [None] * SIZE
|
||||
|
||||
ht_insert(buckets, 'Иван', '123-456')
|
||||
ht_insert(buckets, 'Борис', '789-012')
|
||||
ht_insert(buckets, 'Анна', '345-678')
|
||||
ht_insert(buckets, 'Иван', '111-222')
|
||||
print(ht_list_all(buckets))
|
||||
print(ht_find(buckets, 'Анна'))
|
||||
print(ht_find(buckets, 'Петр'))
|
||||
ht_delete(buckets, 'Борис')
|
||||
print(ht_list_all(buckets))
|
||||
|
|
@ -1,67 +0,0 @@
|
|||
def create_node(name, phone):
|
||||
return {'name': name, 'phone': phone, 'next': None}
|
||||
|
||||
def ll_insert(head, name, phone):
|
||||
current = head
|
||||
while current is not None:
|
||||
if current['name'] == name:
|
||||
current['phone'] = phone
|
||||
return head
|
||||
current = current['next']
|
||||
|
||||
new_node = create_node(name, phone)
|
||||
|
||||
if head is None:
|
||||
return new_node
|
||||
|
||||
current = head
|
||||
while current['next'] is not None:
|
||||
current = current['next']
|
||||
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']
|
||||
|
||||
prev = head
|
||||
current = head['next']
|
||||
while current is not None:
|
||||
if current['name'] == name:
|
||||
prev['next'] = current['next']
|
||||
return head
|
||||
prev = current
|
||||
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 pair: pair[0])
|
||||
return records
|
||||
|
||||
if __name__ == '__main__':
|
||||
head = None
|
||||
head = ll_insert(head, 'Иван', '123-456')
|
||||
head = ll_insert(head, 'Борис', '789-012')
|
||||
head = ll_insert(head, 'Анна', '345-678')
|
||||
head = ll_insert(head, 'Иван', '111-222')
|
||||
print(ll_list_all(head))
|
||||
print(ll_find(head, 'Иван'))
|
||||
print(ll_find(head, 'Петр'))
|
||||
head = ll_delete(head, 'Борис')
|
||||
print(ll_list_all(head))
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 46 KiB |
|
|
@ -1,39 +0,0 @@
|
|||
import pandas as pd
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
|
||||
df = pd.read_csv('experiment_results.csv')
|
||||
|
||||
mean_times = df.groupby(['Structure', 'Mode'])[['Insert (sec)', 'Search (sec)', 'Delete (sec)']].mean().reset_index()
|
||||
|
||||
structures = mean_times['Structure'].unique()
|
||||
modes = mean_times['Mode'].unique()
|
||||
|
||||
fig, axes = plt.subplots(1, 3, figsize=(15, 5))
|
||||
|
||||
operations = ['Insert (sec)', 'Search (sec)', 'Delete (sec)']
|
||||
titles = ['Insertion', 'Search', 'Deletion']
|
||||
|
||||
for ax, op, title in zip(axes, operations, titles):
|
||||
x = np.arange(len(structures))
|
||||
width = 0.35
|
||||
|
||||
random_vals = []
|
||||
sorted_vals = []
|
||||
for s in structures:
|
||||
random_row = mean_times[(mean_times['Structure'] == s) & (mean_times['Mode'] == 'random')]
|
||||
sorted_row = mean_times[(mean_times['Structure'] == s) & (mean_times['Mode'] == 'sorted')]
|
||||
random_vals.append(random_row[op].values[0] if not random_row.empty else 0)
|
||||
sorted_vals.append(sorted_row[op].values[0] if not sorted_row.empty else 0)
|
||||
|
||||
ax.bar(x - width/2, random_vals, width, label='Random')
|
||||
ax.bar(x + width/2, sorted_vals, width, label='Sorted')
|
||||
ax.set_xticks(x)
|
||||
ax.set_xticklabels(structures)
|
||||
ax.set_ylabel('Time (seconds)')
|
||||
ax.set_title(title)
|
||||
ax.legend()
|
||||
|
||||
plt.tight_layout()
|
||||
plt.savefig('performance_comparison.png', dpi=150)
|
||||
plt.show()
|
||||
|
|
@ -1,16 +0,0 @@
|
|||
maze,strategy,time_ms,visited_cells,path_length
|
||||
Small 10x6,BFS,0.05722500009142095,25.0,16.0
|
||||
Small 10x6,DFS,0.05680966667872175,24.0,16.0
|
||||
Small 10x6,AStar,0.04801966664066034,23.0,16.0
|
||||
Medium 10x10,BFS,0.04772166676048073,47.0,16.0
|
||||
Medium 10x10,DFS,0.034641333362136116,44.0,30.0
|
||||
Medium 10x10,AStar,0.0983669999641279,47.0,16.0
|
||||
Large 20x20,BFS,0.09949400002066493,100.0,36.0
|
||||
Large 20x20,DFS,0.07004933331700158,75.0,68.0
|
||||
Large 20x20,AStar,0.16450733316257052,85.0,36.0
|
||||
Empty 15x15,BFS,0.13264433331035738,133.0,17.0
|
||||
Empty 15x15,DFS,0.11371733338213137,161.0,89.0
|
||||
Empty 15x15,AStar,0.1543506666621397,65.0,17.0
|
||||
No exit 10x10,BFS,0.04392100011803753,25.0,0.0
|
||||
No exit 10x10,DFS,0.05871466661725814,25.0,0.0
|
||||
No exit 10x10,AStar,0.046440666665148456,25.0,0.0
|
||||
|
|
|
@ -1,438 +0,0 @@
|
|||
import sys
|
||||
import os
|
||||
from collections import deque
|
||||
import heapq
|
||||
import time
|
||||
import csv
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
|
||||
class GridPoint:
|
||||
def __init__(self, x, y):
|
||||
self.x = x
|
||||
self.y = y
|
||||
self.blocked = False
|
||||
self.is_start = False
|
||||
self.is_exit = False
|
||||
|
||||
def can_step(self):
|
||||
return not self.blocked
|
||||
|
||||
class Labyrinth:
|
||||
def __init__(self, w, h):
|
||||
self.w = w
|
||||
self.h = h
|
||||
self.grid = [[GridPoint(x, y) for x in range(w)] for y in range(h)]
|
||||
self.start_point = None
|
||||
self.exit_point = None
|
||||
|
||||
def get_point(self, x, y):
|
||||
if 0 <= x < self.w and 0 <= y < self.h:
|
||||
return self.grid[y][x]
|
||||
return None
|
||||
|
||||
def set_point(self, x, y, typ):
|
||||
p = self.get_point(x, y)
|
||||
if not p:
|
||||
return
|
||||
if typ == 'wall':
|
||||
p.blocked = True
|
||||
elif typ == 'start':
|
||||
if self.start_point:
|
||||
self.start_point.is_start = False
|
||||
p.is_start = True
|
||||
p.blocked = False
|
||||
self.start_point = p
|
||||
elif typ == 'exit':
|
||||
if self.exit_point:
|
||||
self.exit_point.is_exit = False
|
||||
p.is_exit = True
|
||||
p.blocked = False
|
||||
self.exit_point = p
|
||||
elif typ == 'path':
|
||||
p.blocked = False
|
||||
|
||||
def neighbors(self, p):
|
||||
dirs = [(0, -1), (0, 1), (-1, 0), (1, 0)]
|
||||
res = []
|
||||
for dx, dy in dirs:
|
||||
nx, ny = p.x + dx, p.y + dy
|
||||
nb = self.get_point(nx, ny)
|
||||
if nb and nb.can_step():
|
||||
res.append(nb)
|
||||
return res
|
||||
|
||||
class MazeLoader:
|
||||
def load(self, filename):
|
||||
raise NotImplementedError
|
||||
|
||||
class TextMazeLoader(MazeLoader):
|
||||
def load(self, filename):
|
||||
with open(filename, 'r') as f:
|
||||
lines = [line.rstrip('\n') for line in f]
|
||||
h = len(lines)
|
||||
w = max(len(line) for line in lines) if h > 0 else 0
|
||||
start_cnt = 0
|
||||
exit_cnt = 0
|
||||
lab = Labyrinth(w, h)
|
||||
|
||||
for y, line in enumerate(lines):
|
||||
for x, ch in enumerate(line):
|
||||
if ch == '#':
|
||||
lab.set_point(x, y, 'wall')
|
||||
elif ch == 'S':
|
||||
lab.set_point(x, y, 'start')
|
||||
start_cnt += 1
|
||||
elif ch == 'E':
|
||||
lab.set_point(x, y, 'exit')
|
||||
exit_cnt += 1
|
||||
else:
|
||||
lab.set_point(x, y, 'path')
|
||||
if start_cnt != 1 or exit_cnt != 1:
|
||||
raise ValueError(f"Need exactly one S and one E. Found S={start_cnt}, E={exit_cnt}")
|
||||
return lab
|
||||
|
||||
class SearchAlgorithm:
|
||||
def find_way(self, lab, start, goal):
|
||||
raise NotImplementedError
|
||||
|
||||
def _build_path(self, prev, start, goal):
|
||||
path = []
|
||||
cur = goal
|
||||
while cur:
|
||||
path.append(cur)
|
||||
cur = prev.get(cur)
|
||||
path.reverse()
|
||||
return path
|
||||
|
||||
def get_visited(self):
|
||||
return getattr(self, '_visited', 0)
|
||||
|
||||
class BreadthFirst(SearchAlgorithm):
|
||||
def find_way(self, lab, start, goal):
|
||||
q = deque([start])
|
||||
prev = {start: None}
|
||||
seen = {start}
|
||||
while q:
|
||||
cur = q.popleft()
|
||||
if cur == goal:
|
||||
self._visited = len(seen)
|
||||
return self._build_path(prev, start, goal)
|
||||
for nb in lab.neighbors(cur):
|
||||
if nb not in seen:
|
||||
seen.add(nb)
|
||||
prev[nb] = cur
|
||||
q.append(nb)
|
||||
self._visited = len(seen)
|
||||
return []
|
||||
|
||||
class DepthFirst(SearchAlgorithm):
|
||||
def find_way(self, lab, start, goal):
|
||||
stack = [start]
|
||||
prev = {start: None}
|
||||
seen = {start}
|
||||
while stack:
|
||||
cur = stack.pop()
|
||||
if cur == goal:
|
||||
self._visited = len(seen)
|
||||
return self._build_path(prev, start, goal)
|
||||
for nb in lab.neighbors(cur):
|
||||
if nb not in seen:
|
||||
seen.add(nb)
|
||||
prev[nb] = cur
|
||||
stack.append(nb)
|
||||
self._visited = len(seen)
|
||||
return []
|
||||
|
||||
class AStar(SearchAlgorithm):
|
||||
def _dist(self, a, b):
|
||||
return abs(a.x - b.x) + abs(a.y - b.y)
|
||||
|
||||
def find_way(self, lab, start, goal):
|
||||
heap = []
|
||||
cnt = 0
|
||||
start_f = self._dist(start, goal)
|
||||
heapq.heappush(heap, (start_f, cnt, start))
|
||||
cnt += 1
|
||||
prev = {}
|
||||
g = {start: 0}
|
||||
f = {start: start_f}
|
||||
seen = set()
|
||||
while heap:
|
||||
cur_f, _, cur = heapq.heappop(heap)
|
||||
seen.add(cur)
|
||||
if cur == goal:
|
||||
self._visited = len(seen)
|
||||
return self._build_path(prev, start, goal)
|
||||
if cur_f > f.get(cur, float('inf')):
|
||||
continue
|
||||
for nb in lab.neighbors(cur):
|
||||
new_g = g[cur] + 1
|
||||
if new_g < g.get(nb, float('inf')):
|
||||
prev[nb] = cur
|
||||
g[nb] = new_g
|
||||
new_f = new_g + self._dist(nb, goal)
|
||||
f[nb] = new_f
|
||||
heapq.heappush(heap, (new_f, cnt, nb))
|
||||
cnt += 1
|
||||
self._visited = len(seen)
|
||||
return []
|
||||
|
||||
class LabyrinthSolver:
|
||||
def __init__(self, lab):
|
||||
self.lab = lab
|
||||
self.algorithm = None
|
||||
|
||||
def set_algorithm(self, algo):
|
||||
self.algorithm = algo
|
||||
|
||||
def solve(self):
|
||||
if not self.algorithm:
|
||||
return None
|
||||
t0 = time.perf_counter()
|
||||
path = self.algorithm.find_way(self.lab, self.lab.start_point, self.lab.exit_point)
|
||||
t1 = time.perf_counter()
|
||||
ms = (t1 - t0) * 1000
|
||||
return ms, self.algorithm.get_visited(), len(path)
|
||||
|
||||
class Player:
|
||||
def __init__(self, start, lab):
|
||||
self.current = start
|
||||
self.last = None
|
||||
self.lab = lab
|
||||
|
||||
def move(self, cell):
|
||||
if cell and cell.can_step():
|
||||
self.last = self.current
|
||||
self.current = cell
|
||||
return True
|
||||
return False
|
||||
|
||||
def undo(self):
|
||||
if self.last:
|
||||
self.current, self.last = self.last, None
|
||||
return True
|
||||
return False
|
||||
|
||||
class Command:
|
||||
def do(self):
|
||||
raise NotImplementedError
|
||||
def revert(self):
|
||||
raise NotImplementedError
|
||||
|
||||
class MoveCommand(Command):
|
||||
def __init__(self, player, dx, dy, lab):
|
||||
self.player = player
|
||||
self.dx = dx
|
||||
self.dy = dy
|
||||
self.lab = lab
|
||||
self.done = False
|
||||
|
||||
def do(self):
|
||||
nx = self.player.current.x + self.dx
|
||||
ny = self.player.current.y + self.dy
|
||||
target = self.lab.get_point(nx, ny)
|
||||
if target and target.can_step():
|
||||
self.player.move(target)
|
||||
self.done = True
|
||||
return True
|
||||
return False
|
||||
|
||||
def revert(self):
|
||||
if self.done:
|
||||
self.player.undo()
|
||||
self.done = False
|
||||
return True
|
||||
return False
|
||||
|
||||
class InteractiveView:
|
||||
def __init__(self, lab, player):
|
||||
self.lab = lab
|
||||
self.player = player
|
||||
|
||||
def render(self):
|
||||
os.system('cls' if os.name == 'nt' else 'clear')
|
||||
print("=" * (self.lab.w * 2 + 4))
|
||||
print(" LABYRINTH (P = player)")
|
||||
print("=" * (self.lab.w * 2 + 4))
|
||||
for y in range(self.lab.h):
|
||||
print(" ", end='')
|
||||
for x in range(self.lab.w):
|
||||
p = self.lab.get_point(x, y)
|
||||
if self.player.current == p:
|
||||
print('P', end=' ')
|
||||
elif p == self.lab.start_point:
|
||||
print('S', end=' ')
|
||||
elif p == self.lab.exit_point:
|
||||
print('E', end=' ')
|
||||
elif p.blocked:
|
||||
print('#', end=' ')
|
||||
else:
|
||||
print('.', end=' ')
|
||||
print()
|
||||
print("=" * (self.lab.w * 2 + 4))
|
||||
print(f" Position: ({self.player.current.x},{self.player.current.y})")
|
||||
print(" Controls: h(left) j(down) k(up) l(right) u=undo q=quit")
|
||||
print(" Auto-search: b=BFS d=DFS a=A*")
|
||||
|
||||
def run_experiment(maze_file, algo, runs=5):
|
||||
loader = TextMazeLoader()
|
||||
lab = loader.load(maze_file)
|
||||
total_ms = 0
|
||||
total_visited = 0
|
||||
total_len = 0
|
||||
for _ in range(runs):
|
||||
solver = LabyrinthSolver(lab)
|
||||
solver.set_algorithm(algo)
|
||||
stats = solver.solve()
|
||||
if stats:
|
||||
ms, vis, plen = stats
|
||||
total_ms += ms
|
||||
total_visited += vis
|
||||
total_len += plen
|
||||
return total_ms / runs, total_visited / runs, total_len / runs
|
||||
|
||||
def generate_plots(results):
|
||||
mazes = list(set([r['maze'] for r in results]))
|
||||
strategies = ['BFS', 'DFS', 'AStar']
|
||||
|
||||
fig, axes = plt.subplots(1, 3, figsize=(15, 5))
|
||||
x = np.arange(len(mazes))
|
||||
width = 0.25
|
||||
|
||||
for i, strat in enumerate(strategies):
|
||||
times = []
|
||||
for maze in mazes:
|
||||
val = next((r['time_ms'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
|
||||
times.append(val)
|
||||
axes[0].bar(x + i*width, times, width, label=strat)
|
||||
axes[0].set_xlabel('Maze')
|
||||
axes[0].set_ylabel('Time (ms)')
|
||||
axes[0].set_title('Execution Time')
|
||||
axes[0].set_xticks(x + width)
|
||||
axes[0].set_xticklabels(mazes, rotation=45, ha='right')
|
||||
axes[0].legend()
|
||||
axes[0].grid(True, alpha=0.3)
|
||||
|
||||
for i, strat in enumerate(strategies):
|
||||
visited = []
|
||||
for maze in mazes:
|
||||
val = next((r['visited_cells'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
|
||||
visited.append(val)
|
||||
axes[1].bar(x + i*width, visited, width, label=strat)
|
||||
axes[1].set_xlabel('Maze')
|
||||
axes[1].set_ylabel('Visited Cells')
|
||||
axes[1].set_title('Visited Cells')
|
||||
axes[1].set_xticks(x + width)
|
||||
axes[1].set_xticklabels(mazes, rotation=45, ha='right')
|
||||
axes[1].legend()
|
||||
axes[1].grid(True, alpha=0.3)
|
||||
|
||||
for i, strat in enumerate(strategies):
|
||||
lengths = []
|
||||
for maze in mazes:
|
||||
val = next((r['path_length'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
|
||||
lengths.append(val)
|
||||
axes[2].bar(x + i*width, lengths, width, label=strat)
|
||||
axes[2].set_xlabel('Maze')
|
||||
axes[2].set_ylabel('Path Length')
|
||||
axes[2].set_title('Path Length')
|
||||
axes[2].set_xticks(x + width)
|
||||
axes[2].set_xticklabels(mazes, rotation=45, ha='right')
|
||||
axes[2].legend()
|
||||
axes[2].grid(True, alpha=0.3)
|
||||
|
||||
plt.tight_layout()
|
||||
plt.savefig('performance_comparison.png', dpi=150, bbox_inches='tight')
|
||||
plt.show()
|
||||
|
||||
if __name__ == "__main__":
|
||||
if len(sys.argv) > 1 and sys.argv[1] == 'experiment':
|
||||
print("Running experiments on all mazes...")
|
||||
maze_files = [
|
||||
("maze/maze1.txt", "Small 10x6"),
|
||||
("maze/maze10x10.txt", "Medium 10x10"),
|
||||
("maze/maze20x20.txt", "Large 20x20"),
|
||||
("maze/maze_empty.txt", "Empty 15x15"),
|
||||
("maze/maze_no_exit.txt", "No exit 10x10")
|
||||
]
|
||||
algorithms = [
|
||||
("BFS", BreadthFirst()),
|
||||
("DFS", DepthFirst()),
|
||||
("AStar", AStar())
|
||||
]
|
||||
results = []
|
||||
for fname, label in maze_files:
|
||||
print(f"Testing {label}...")
|
||||
for aname, algo in algorithms:
|
||||
try:
|
||||
avg_t, avg_v, avg_l = run_experiment(fname, algo, runs=3)
|
||||
results.append({
|
||||
'maze': label,
|
||||
'strategy': aname,
|
||||
'time_ms': avg_t,
|
||||
'visited_cells': avg_v,
|
||||
'path_length': avg_l
|
||||
})
|
||||
print(f" {aname}: time={avg_t:.3f}ms visited={avg_v:.0f} length={avg_l:.0f}")
|
||||
except Exception as e:
|
||||
print(f" {aname}: ERROR {e}")
|
||||
# save csv
|
||||
with open('experiment_results.csv', 'w', newline='', encoding='utf-8') as f:
|
||||
writer = csv.DictWriter(f, fieldnames=['maze', 'strategy', 'time_ms', 'visited_cells', 'path_length'])
|
||||
writer.writeheader()
|
||||
writer.writerows(results)
|
||||
generate_plots(results)
|
||||
print("Done. Results saved to experiment_results.csv and performance_comparison.png")
|
||||
sys.exit(0)
|
||||
|
||||
# else interactive mode
|
||||
loader = TextMazeLoader()
|
||||
lab = loader.load("maze/maze1.txt")
|
||||
player = Player(lab.start_point, lab)
|
||||
view = InteractiveView(lab, player)
|
||||
view.render()
|
||||
|
||||
solver = LabyrinthSolver(lab)
|
||||
history = []
|
||||
|
||||
while True:
|
||||
key = input("\n > ").lower()
|
||||
if key == 'q':
|
||||
print("Goodbye!")
|
||||
break
|
||||
elif key == 'b':
|
||||
solver.set_algorithm(BreadthFirst())
|
||||
ms, vis, plen = solver.solve()
|
||||
print(f"BFS: {ms:.3f}ms, visited={vis}, length={plen}")
|
||||
elif key == 'd':
|
||||
solver.set_algorithm(DepthFirst())
|
||||
ms, vis, plen = solver.solve()
|
||||
print(f"DFS: {ms:.3f}ms, visited={vis}, length={plen}")
|
||||
elif key == 'a':
|
||||
solver.set_algorithm(AStar())
|
||||
ms, vis, plen = solver.solve()
|
||||
print(f"A*: {ms:.3f}ms, visited={vis}, length={plen}")
|
||||
elif key in ('h','j','k','l'):
|
||||
moves = {'h': (-1,0), 'l': (1,0), 'k': (0,-1), 'j': (0,1)}
|
||||
dx, dy = moves[key]
|
||||
cmd = MoveCommand(player, dx, dy, lab)
|
||||
if cmd.do():
|
||||
history.append(cmd)
|
||||
view.render()
|
||||
if player.current == lab.exit_point:
|
||||
print("\n*** YOU REACHED THE EXIT! ***")
|
||||
print(f"Total moves: {len(history)}")
|
||||
break
|
||||
else:
|
||||
print("Can't go there - wall!")
|
||||
elif key == 'u':
|
||||
if history:
|
||||
cmd = history.pop()
|
||||
cmd.revert()
|
||||
view.render()
|
||||
print("Undo last move")
|
||||
else:
|
||||
print("Nothing to undo")
|
||||
else:
|
||||
print("Unknown command")
|
||||
|
|
@ -1,7 +0,0 @@
|
|||
##########
|
||||
#S #
|
||||
# ####### #
|
||||
# # # #
|
||||
# # ### # #
|
||||
# # E #
|
||||
##########
|
||||
|
|
@ -1,10 +0,0 @@
|
|||
##########
|
||||
#S #
|
||||
# # #### #
|
||||
# # #
|
||||
# #### # #
|
||||
# # #
|
||||
# #### # #
|
||||
# # #
|
||||
# #
|
||||
########E#
|
||||
|
|
@ -1,21 +0,0 @@
|
|||
####################
|
||||
#S #
|
||||
# ############### #
|
||||
# # # #
|
||||
# # ######### # # #
|
||||
# # # # # # #
|
||||
# # # ##### # # # #
|
||||
# # # # # # # # #
|
||||
# # # # # # # # # #
|
||||
# # # # # # # # #
|
||||
# # # ##### # # # #
|
||||
# # # # # # #
|
||||
# # ######### # # #
|
||||
# # # #
|
||||
# ############### #
|
||||
# #
|
||||
# ############### #
|
||||
# # # #
|
||||
# # ########### # #
|
||||
# E#
|
||||
####################
|
||||
|
|
@ -1,15 +0,0 @@
|
|||
###############
|
||||
#S #
|
||||
# #
|
||||
# #
|
||||
# #
|
||||
# #
|
||||
# #
|
||||
# #
|
||||
# #
|
||||
# #
|
||||
# #
|
||||
# #
|
||||
# #
|
||||
# E #
|
||||
###############
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue
Block a user