Refactor knight.py and main.py

Units/knight.py

@@ -21,6 +21,11 @@ class Knight:
         self.direction = 2
         self.visited = [self.position]
         self.starting_position = (position)
+        self.already_tried = []
+
+    def  move(self, target):
+        pass
+
 
     def ai(self):
         screen_x, screen_y = self.engine.iso_transform(*self.position)
@@ -33,66 +38,15 @@ class Knight:
                 screen_y += (screen_y_dest - screen_y) * self.partial_move
             else:
                 screen_x, screen_y = self.engine.iso_transform(*self.destination)
-                
                 neighbors_list = self.engine.find_neighbors(self.destination) # Get the neighbors of the destination cell
-                
                 # Remove any neighbors that are not walkable
                 neighbors_list = [cell for cell in neighbors_list if self.engine.battlefield[cell[1]][cell[0]].walkable]
-
+                # Update position and visited list
-                old_distance_from_target = self.engine.get_distance(self.destination,self.target)
-                old_distance_from_start = self.engine.get_distance(self.destination,self.starting_position)
-
-                for cell_visited in self.visited:
-                    if cell_visited in neighbors_list:
-                        neighbors_list.remove(cell_visited)
-
-                #self.visited = self.visited[-2:]
                 self.position = self.destination
+                self.destination = None
                 self.visited.append(self.position)
-
+                self.destination = self.engine.get_closest_neighbor(neighbors_list,self.target)
-                for cell in neighbors_list:
+                self.partial_move = 0
-                   self.engine.effects.append(OrderClick(self.engine.iso_transform(*cell),color="lightblue"))
-                for cell in self.visited:
-                   self.engine.effects.append(OrderClick(self.engine.iso_transform(*cell),color="red"))
-
-                if not neighbors_list:
-                    print("No neighbors")
-                    #neighbors_list.append(self.visited)
-                    #self.target = self.position
-                    self.destination = None
-
-                else:
-                    self.destination = self.engine.get_closest_neighbor(neighbors_list,self.target)
-                    new_distance_from_target = self.engine.get_distance(self.destination,self.target)
-                    new_distance_from_start = self.engine.get_distance(self.destination,self.starting_position)
-                    if new_distance_from_target >= old_distance_from_target or new_distance_from_start < old_distance_from_start:
-                        print(f"{time.time()} - No progress")
-                        new_neighbors_list = []
-                        for neighbor in neighbors_list:
-                            neighbor_neighbors_list = self.engine.find_neighbors(neighbor)
-                            for neighbor_neighbor in neighbor_neighbors_list:
-                            # consider only the neighbors of the neighbors that are walkable
-                                if not self.engine.battlefield[neighbor_neighbor[1]][neighbor_neighbor[0]].walkable:
-                                    if neighbor_neighbor not in self.visited:
-                                        # if the neighbor of the neighbor is not walkable and has not been visited, add it to the list of visited cells
-                                        new_neighbors_list.append(neighbor)
-                                        break
-                        # scegli uhn vicino casualmente come destinaziione  
-                        
-                        self.destination = new_neighbors_list[random.randint(0,len(new_neighbors_list)-1)]
-
-                if self.destination:                 
-                    self.engine.effects.append(OrderClick(self.engine.iso_transform(*self.destination),color="purple"))
-                    self.partial_move = 0
-                    if  self.position != self.target:
-                        self.direction = self.engine.get_direction(self.position,self.destination)
-                else:
-                    print("No destination")
-                    self.visited = [self.position]
-                    self.destination = self.position
-                    #self.target = self.position
-                    self.engine.effects.append(OrderClick(self.engine.iso_transform(*self.destination),color="brown"))
-
         else:
             self.visited = [self.target]
             self.position = self.target
@@ -101,4 +55,8 @@ class Knight:
             self.state = "Idle"
             self.partial_move = 1
         gif = self.animation.get(f'Knight_{self.state}_dir{self.direction}.gif')
-        return gif, screen_x, screen_y
+        return gif, screen_x, screen_y
+    
+    def move_to(self, target):
+        self.target = target
+        self.state = "Walk"

main.py

@@ -7,6 +7,7 @@ import json
 from Units.knight import Knight
 from Effects.order_click import OrderClick
 from tkinter import Menu
+from collections import deque
 
 
 
@@ -141,7 +142,40 @@ class IsometricGame:
         x1, y1 = position1
         x2, y2 = position2
         return abs(((x2 - x1) ** 2 + (y2 - y1) ** 2) ** 0.5)
-    
+    def get_distance_components(self, position1, position2):
+        x1, y1 = position1
+        x2, y2 = position2
+        return abs(x2 - x1), abs(y2 - y1)
+    #function to check if a cell is near a wall
+    def near_wall(self, position):
+        x, y = position
+        neighbors = self.find_neighbors(position)
+        for neighbor in neighbors:
+            if not self.battlefield[neighbor[1]][neighbor[0]].walkable:
+                return True
+    def min_steps_to_target(self, start, target):
+        grid = [[0 for _ in range(self.width)] for _ in range(self.height)]
+        rows, cols = len(grid), len(grid[0])
+        dx = [0, 1, 0, -1]
+        dy = [1, 0, -1, 0]
+        queue = deque([start])
+        visited = set([start])
+
+        steps = 0
+        while queue:
+            for _ in range(len(queue)):
+                x, y = queue.popleft()
+                if (x, y) == target:
+                    return steps
+
+                for i in range(4):
+                    nx, ny = x + dx[i], y + dy[i]
+                    if 0 <= nx < rows and 0 <= ny < cols and (nx, ny) not in visited:
+                        queue.append((nx, ny))
+                        visited.add((nx, ny))
+            steps += 1
+
+        return -1      
     def draw_battlefield(self):
         self.canvas.delete("cell")  # Pulisce le celle precedenti prima di ridisegnare
         self.canvas.delete("cell-label") 
@@ -235,6 +269,7 @@ class IsometricGame:
         # calculate the clicked cell's coordinates
         cell_x, cell_y = self.inv_iso_transform(event.x, event.y)
         self.battlefield[cell_y][cell_x].walkable ^= True
+        self.battlefield[cell_y][cell_x].tile = self.tiles["landscapeTiles_067"] if self.battlefield[cell_y][cell_x].walkable else self.tiles["landscapeTiles_066"]
         self.draw_battlefield()
         self.draw_units()
 
@@ -260,10 +295,8 @@ class IsometricGame:
             return
 
         if 0 <= cell_x < self.width and 0 <= cell_y < self.height:
-            self.knight.starting_position = self.knight.position
+            self.knight.move_to((cell_x,cell_y))
-            self.knight.target = (cell_x,cell_y)
+            
-            self.knight.state = "Walk"
-
     def run(self):
         self.draw_battlefield()
         self.update()
@@ -288,6 +321,17 @@ class Cell:
 if __name__ == "__main__":
     with open('maze.json', 'r') as file:
         data = json.load(file)
+    # Creare una matrice 10x10 piena di False
+    room = [[True for _ in range(10)] for _ in range(10)]
+
+    # Cambiare i valori interni della matrice in True
+    for i in range(1, 9):
+        for j in range(1, 8):
+            room[i][j] = False
+
+    # Creare un'apertura di un'unità verso l'esterno
+    room[0][4] = True  # Cambia questo valore per spostare l'apertura
+    data =room
     # data is a boolean matrix, find dmensions
     width = len(data[0])
     height = len(data)

solver.py

@@ -70,5 +70,6 @@ class MazeSolver:
         self.window.mainloop()
 
 # Create and run the maze solver
+        #Breadth-First Search, BFS
 solver = MazeSolver('maze.json')
 solver.run()