[2] Стратегии поиска пути

BorisovMI/lab_2/docs/data/maze.py

@@ -120,3 +120,114 @@ class TextileMazeBuilder(MazeBuilder):
         
         return maze
 
+class PathFindingStrategy:
+    def findPath(self, maze, start, exit):
+        pass
+
+
+class BFSStrategy(PathFindingStrategy):
+    def findPath(self, maze, start, exit):
+        if exit is None:
+            return []
+        queue = deque([start])
+        visited = {start}
+        parent = {start: None}
+        
+        while queue:
+            current = queue.popleft()
+            
+            if current == exit:
+                return self._reconstruct_path(parent, start, exit)
+            
+            for neighbor in maze.getNeighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    parent[neighbor] = current
+                    queue.append(neighbor)
+        
+        return []  
+    
+    def _reconstruct_path(self, parent, start, exit):
+        path = []
+        current = exit
+        while current is not None:
+            path.append(current)
+            current = parent[current]
+        path.reverse()
+        return path
+
+
+class DFSStrategy(PathFindingStrategy):
+    def findPath(self, maze, start, exit):
+        if exit is None:
+            return []
+        stack = [start]
+        visited = {start}
+        parent = {start: None}
+        
+        while stack:
+            current = stack.pop()
+            
+            if current == exit:
+                return self._reconstruct_path(parent, start, exit)
+            
+            for neighbor in maze.getNeighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    parent[neighbor] = current
+                    stack.append(neighbor)
+        
+        return []
+    
+    def _reconstruct_path(self, parent, start, exit):
+        path = []
+        current = exit
+        while current is not None:
+            path.append(current)
+            current = parent[current]
+        path.reverse()
+        return path
+
+
+class AStrategy(PathFindingStrategy):
+    def _heuristic(self, cell, exit):
+        if exit is None:
+            return 0
+        return abs(cell.x - exit.x) + abs(cell.y - exit.y)
+    
+    def findPath(self, maze, start, exit):
+        if exit is None:
+            return []
+        open_set = []
+        heapq.heappush(open_set, (0, start))
+        
+        came_from = {start: None}
+        g_score = {start: 0}
+        
+        while open_set:
+            current = heapq.heappop(open_set)[1]
+            
+            if current == exit:
+                return self._reconstruct_path(came_from, start, exit)
+            
+            for neighbor in maze.getNeighbors(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 = tentative_g + self._heuristic(neighbor, exit)
+                    heapq.heappush(open_set, (f_score, neighbor))
+        
+        return []
+    
+    def _reconstruct_path(self, came_from, start, exit):
+        path = []
+        current = exit
+        while current is not None:
+            path.append(current)
+            current = came_from[current]
+        path.reverse()
+        return path
+
+