2026-rff_mp/romanovpv/task 2/docs/data/strategies.py
2026-05-18 22:10:10 +03:00

156 lines
4.1 KiB
Python

from abc import ABC, abstractmethod
from collections import deque
import heapq
class PathFindingStrategy(ABC):
@abstractmethod
def findPath(self, maze, start, exit_cell):
pass
def restorePath(
self,
parent,
start,
exit_cell
):
path = []
current = exit_cell
while current != start:
path.append(current)
current = parent[current]
path.append(start)
path.reverse()
return path
class BFSStrategy(PathFindingStrategy):
def findPath(
self,
maze,
start,
exit_cell
):
queue = deque([start])
visited = {start}
parent = {}
while queue:
current = queue.popleft()
if current == exit_cell:
return (
self.restorePath(
parent,
start,
exit_cell),
len(visited)
)
for neighbor in maze.getNeighbors(current):
if neighbor not in visited:
visited.add(
neighbor
)
parent[
neighbor
] = current
queue.append(
neighbor
)
return [], len(visited)
class DFSStrategy(PathFindingStrategy):
def findPath(
self,
maze,
start,
exit_cell
):
stack = [start]
visited = {start}
parent = {}
while stack:
current = stack.pop()
if current == exit_cell:
return (self.restorePath
(
parent,
start,
exit_cell),
len(visited)
)
for neighbor in maze.getNeighbors(current):
if neighbor not in visited:
visited.add(
neighbor
)
parent[
neighbor
] = current
stack.append(
neighbor
)
return [], len(visited)
class AStarStrategy(PathFindingStrategy):
def heuristic(
self,
cell,
exit_cell
):
return (abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y))
def findPath(
self,
maze,
start,
exit_cell
):
pq = []
heapq.heappush(
pq,
(
0,
id(start),
start
)
)
parent = {}
g_score = {
start: 0
}
visited = set()
while pq:
_, _, current = (
heapq.heappop(
pq
)
)
if current in visited:
continue
visited.add(
current
)
if current == exit_cell:
return (self.restorePath(
parent,
start,
exit_cell),
len(visited)
)
for neighbor in maze.getNeighbors(current):
new_cost = (
g_score[current]
+ 1
)
if (neighbor not in g_score or new_cost < g_score[neighbor] ):
g_score[neighbor
] = new_cost
parent[
neighbor
] = current
priority = (new_cost + self.heuristic(neighbor, exit_cell)
)
heapq.heappush(
pq,
(
priority,
id(neighbor),
neighbor
)
)
return [], len(visited)