feat: After arriving at selected by user tile, Tractor makes decision by using decision tree.

The decision is printed in terminal.

src/main.py

@@ -1,7 +1,7 @@
 import pygame
 from field import Field
 import os
-from config import TILE_SIZE, TICK_RATE
+from config import TILE_SIZE, TICK_RATE, FINAL_X, FINAL_Y
 
 if __name__ == "__main__":
     pygame.init()
@@ -13,10 +13,19 @@ if __name__ == "__main__":
     field = Field()
     
     running = True
+
     while running:
         for event in pygame.event.get():
             if event.type == pygame.QUIT:
                 running = False
+            if event.type == pygame.MOUSEBUTTONDOWN:
+                x, y = pygame.mouse.get_pos()
+                print(f"Mouse clicked at: ({x}, {y})")
+                
+                grid_x = x // TILE_SIZE
+                grid_y = y // TILE_SIZE
+                
+                field.tractor.set_new_goal((grid_x, grid_y))
         
         field.tractor.update()
         screen.fill(WHITE)

src/tractor.py

@@ -18,30 +18,33 @@ class Tractor(pygame.sprite.Sprite):
     def __init__(self, field):
         super().__init__
         self.field = field
-
+        self.water = 50
         self.image = pygame.image.load('images/tractor/east.png').convert_alpha()
         self.image = pygame.transform.scale(self.image, (TILE_SIZE, TILE_SIZE))
         self.rect = self.image.get_rect()
-
-        self.direction = STARTING_DIRECTION
-        # TODO: enable tractor to start on other tile than (0,0)
-        self.start = (START_X, START_Y)
-        self.final = (FINAL_X, FINAL_Y)
+        self.direction = 'east'
+        self.start = (0, 0)
+        self.final = (0, 0)
         print('destination @', self.final[0], self.final[1])
         self.rect.topleft = (self.start[0] * TILE_SIZE, self.start[1] * TILE_SIZE)
 
-        self.water = 50
-
-        # A-STAR
-        # came_from, total_cost = self.a_star()
-        # path = self.reconstruct_path(came_from)
-        # self.actions = self.recreate_actions(path)
-        # self.action_index = 0
+        self.rect.topleft = (self.start[0] * TILE_SIZE, self.start[1] * TILE_SIZE)
+        self.actions = []
+        self.action_index = 0
 
         # DECISION TREE:
         self.label_encoders = {}
         self.load_decision_tree_model()
 
+    def set_new_goal(self, goal):
+        self.start = self.get_coordinates()
+        self.final = goal
+        came_from, total_cost = self.a_star()
+        path = self.reconstruct_path(came_from)
+        self.actions = self.recreate_actions(path)
+        self.action_index = 0
+        print(f"New goal set to: {self.final}")
+
     def load_decision_tree_model(self):
         data = pd.read_csv('tree.csv')
 
@@ -94,13 +97,11 @@ class Tractor(pygame.sprite.Sprite):
     def draw(self, surface):
         surface.blit(self.image, self.rect)
 
-
     def get_coordinates(self):
         x = self.rect.x // TILE_SIZE
         y = self.rect.y // TILE_SIZE
         return (x,y)
 
-
     def move(self):
         if self.direction == "north" and self.rect.y > 0:
             self.rect.y -= TILE_SIZE
@@ -162,29 +163,16 @@ class Tractor(pygame.sprite.Sprite):
             self.move()
         else:
             self.move()
-
-    def update(self):
-        # A STAR:
-        # if self.action_index == len(self.actions):
-        #     return 
-        # action = self.actions[self.action_index]
-
-        # match (action):
-        #     case ('move'):
-        #         self.move()
-        #     case ('left'):
-        #         self.rotate('left')
-        #     case ('right'):
-        #         self.rotate('right')
-
-        # DECISION TREE:
+    
+    def decision_tree(self):
         action = self.make_decision()
-        if (self.get_current_tile().type != 'grass' or self.get_current_tile().type == 'water'): action = 'move'
+        if (self.get_current_tile().type != 'grass' or self.get_current_tile().type == 'water'): action = 'nothing'
         self.prev_action = action
 
+        print("Decyzja podjęta przez drzewo decyzyjne: ", action)
 
         match (action):
-            case ('move'):
+            case ('nothing'):
                 pass
                 #self.move_rotating()
             case ('harvest'):
@@ -241,8 +229,22 @@ class Tractor(pygame.sprite.Sprite):
                 self.get_current_tile().set_type('szpinak')
             case ('plant(ziemniak)'):
                 self.get_current_tile().set_type('ziemniak')
-        self.move_2()
-        #self.action_index += 1
+
+    def update(self):
+        # A STAR:
+        if self.action_index == len(self.actions):
+            return 
+        action = self.actions[self.action_index]
+
+        match (action):
+            case ('move'):
+                self.move()
+            case ('left'):
+                self.rotate('left')
+            case ('right'):
+                self.rotate('right')
+
+        self.action_index += 1
 
         if self.get_current_tile().type == "grass":
             print("Co jest faktycznie: trawa")
@@ -252,9 +254,13 @@ class Tractor(pygame.sprite.Sprite):
             print("Rozpoznano: ", self.get_current_tile().prediction)
             print("Co jest faktycznie: ", self.get_current_tile().type)
         print("\n")
+
+        if self.get_coordinates() == self.final:
+            self.decision_tree()
         
         return
     
+
     def log_info(self):
         # print on what tile type the tractor is on
         x = self.rect.x // TILE_SIZE
@@ -367,13 +373,12 @@ class Tractor(pygame.sprite.Sprite):
             if current == self.final:
                 break
 
-            # next_node: tuple[int, int]
             for next_node in self.neighboring_nodes(coordinates=current):
                 enter_cost = self.cost_of_entering_node(coordinates=next_node)
-                new_cost: int = cost_so_far[current] + enter_cost
+                new_cost = cost_so_far[current] + enter_cost
                 if next_node not in cost_so_far or new_cost < cost_so_far[next_node]:
                     cost_so_far[next_node] = new_cost
-                    priority = new_cost + self.manhattan_cost(current)
+                    priority = new_cost + self.manhattan_cost(next_node)
                     heapq.heappush(fringe, (priority, next_node))
                     came_from[next_node] = current