Fix a_star goaltest and heuristic function

app/__init__.py

@@ -1,5 +1,6 @@
 #!/usr/bin/python3
 import copy
+import random
 from queue import Queue, PriorityQueue
 from threading import Event
 
@@ -44,7 +45,6 @@ class App:
 
         if keys[pygame.K_w]:
             self.__tractor.move()
-            self.__tractor.choose_action()
             print(self.__tractor)
 
         if keys[pygame.K_n]:
@@ -87,27 +87,36 @@ class App:
                 self.__bot_is_running.set()
                 self.__tractor.run_bot_handler(self.__moves, self.__bot_is_running)
 
+        if keys[pygame.K_a]:
+            self.auto_moving()
+
     def update_screen(self) -> None:
         pygame.display.flip()
 
     def quit(self) -> None:
         pygame.quit()
 
+    def auto_moving(self) -> None:
+        self.__tractor.choose_action()
+
     def get_moves_by_a_star(self) -> None:
         x, y = self.__tractor.get_position()
         node = Node(None, x, y, self.__tractor.get_direction(), 0, "movement", "initial state")
         board = copy.deepcopy(self.__board)
-        self.__moves = AStar.search(PriorityQueue(), Queue(), node,
-                                       lambda n=node, b=board: AStar.succ(n, b),
-                                       lambda n=node: AStar.goaltest(n), board)
+        x1 = random.randint(0, HORIZONTAL_NUM_OF_FIELDS)
+        y1 = random.randint(0, VERTICAL_NUM_OF_FIELDS)
+        dest = (x1, y1)
+        self.__moves = AStar.search_solution(PriorityQueue(), Queue(), dest, node,
+                                             lambda n=node, b=board: AStar.succ(n, b),
+                                             lambda d=dest, n=node: AStar.goaltest_by_coords(d, n), board)
 
     def get_moves_by_bfs(self) -> None:
         x, y = self.__tractor.get_position()
         node = Node(None, x, y, self.__tractor.get_direction(), 0, "movement", "initial state")
         board = copy.deepcopy(self.__board)
         self.__moves = Bfs.search(Queue(), Queue(), node,
-                              lambda n=node, b=board: Bfs.succ(n, b),
-                              lambda n=node: Bfs.goaltest(n), board)
+                                  lambda n=node, b=board: Bfs.succ(n, b),
+                                  lambda n=node: Bfs.goaltest(n), board)
 
     def run(self) -> None:
         self.initialize()

app/a_star.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import copy
+import math
 from typing import Callable, Union
 from queue import Queue, PriorityQueue
 
@@ -10,7 +11,7 @@ from app.graphsearch import Node, Graphsearch
 
 
 class PriorityItem:
-    def __init__(self, node: Node, priority: int):
+    def __init__(self, node: Node, priority: float):
         self.node = node
         self.priority = priority
 
@@ -46,7 +47,7 @@ class AStar(Graphsearch):
             fringe.put(tmp_queue.get())
 
     @staticmethod
-    def replace_nodes(fringe: PriorityQueue[PriorityItem], priority: int, state: tuple[int, int, float]):
+    def replace_nodes(fringe: PriorityQueue[PriorityItem], priority: float, state: tuple[int, int, float]):
         fringe_items = AStar.convert_queue_of_priority_items_with_priority_to_list(fringe)
         for s in fringe_items:
             if s[:-1] == state[:-1]:
@@ -57,7 +58,7 @@ class AStar(Graphsearch):
                     break
 
     @staticmethod
-    def g(board: Board, node: Node) -> int:
+    def g(board: Board, node: Node) -> float:
         """cost function"""
         result = 0
         while node.get_node() is not None:
@@ -67,20 +68,28 @@ class AStar(Graphsearch):
         return result
 
     @staticmethod
-    def h(node: Node) -> int:
+    def h(destination: tuple[int, int], node: Node) -> float:
         """heuristic function"""
-        crops_to_harvested = AMOUNT_OF_CROPS - node.get_amount_of_harvested_crops()
-        return crops_to_harvested ** 2 + crops_to_harvested * 10
+        return round(math.sqrt(abs(destination[0] - node.get_x())**2 + abs(destination[0] - node.get_y())**2), 2)
 
     @staticmethod
-    def f(board: Board, node: Node) -> int:
+    def f(board: Board, destination: tuple[int, int], node: Node) -> float:
         """evaluation function"""
-        return AStar.g(board, node) + AStar.h(node)
+        return AStar.g(board, node) + AStar.h(destination, node)
 
     @staticmethod
-    def search(fringe: PriorityQueue, explored: Queue, istate: Node,
+    def goaltest_by_coords(destination: tuple[int, int], item: Node) -> bool:
+        # print(item)
+        # print(destination)
+        if destination[0] == item.get_x() and destination[1] == item.get_y():
+            return True
+        else:
+            return False
+
+    @staticmethod
+    def search_solution(fringe: PriorityQueue, explored: Queue, destination: tuple[int, int], istate: Node,
                succ: Callable[[Node, Board], list],
-               goaltest: Callable[[Node], bool], board: Board) -> Union[bool, list]:
+               goaltest: Callable[[tuple[int,int], Node], bool], board: Board) -> Union[bool, list]:
 
         print(f"Start A*")
         fringe.put(PriorityItem(istate, 0))
@@ -90,7 +99,7 @@ class AStar(Graphsearch):
                 return False
 
             item = fringe.get()
-            if goaltest(item.node):
+            if goaltest(destination, item.node):
                 return AStar.get_all_moves(item.node)
 
             copied_item = copy.deepcopy(item)
@@ -102,7 +111,7 @@ class AStar(Graphsearch):
                 explored_items = AStar.convert_queue_of_priority_items_to_list(explored)
 
                 n = Node(item.node, *state, *action)
-                priority = AStar.f(board, n)
+                priority = AStar.f(board, destination, n)
                 # print(priority)
                 if state[:-1] not in fringe_items and state[:-1] not in explored_items:
                     fringe.put(PriorityItem(n, priority))

app/tractor.py

@@ -309,7 +309,7 @@ class Tractor(BaseField):
 
         is_running.clear()
 
-    def choose_action(self) -> None:
+    def choose_action(self) -> tuple[tuple[int,int],str]:
         vectors = self.__board.convert_fields_to_vectors()
         print(vectors)
         coords = None
@@ -321,6 +321,4 @@ class Tractor(BaseField):
                     coords = (i, j)
                     break
         print(coords, action)
-        if coords is not None:
-            # astar coords
-            pass
+        return coords, action

config.py

@@ -86,10 +86,10 @@ A_DO_NOTHING = "do nothing"
 TYPES_OF_ACTION = [A_SOW, A_HARVEST, A_HYDRATE, A_FERTILIZE, A_DO_NOTHING]
 
 # Costs fields:
-VALUE_OF_CROPS = 1
-VALUE_OF_PLANT = 4
-VALUE_OF_SAND = 7
-VALUE_OF_CLAY = 10
+VALUE_OF_CROPS = 0.25
+VALUE_OF_PLANT = 0.5
+VALUE_OF_SAND = 0.75
+VALUE_OF_CLAY = 1
 
 # Weather
 W_SUNNY = 'Sunny'