optimal goaltest TODO

This commit is contained in:
Tomasz Adamczyk 2021-04-24 00:04:19 +02:00
parent 06e30867c3
commit 56bebed942
10 changed files with 182 additions and 21 deletions

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128
astar.py Normal file
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@ -0,0 +1,128 @@
from operator import itemgetter
import copy
import tractor
class Istate: #stan początkowy traktora (strona, w którą patrzy, miejsce, w którym się on znajduje)
def __init__(self, direction, x, y):
self.direction = direction
self.x = x
self.y = y
def get_direction(self):
return self.direction
def set_direction(self, direction):
self.direction = direction
def get_x(self):
return self.x
def set_x(self, x):
self.x = x
def get_y(self):
return self.y
def set_y(self, y):
self.y = y
class Node: #wierzchołek grafu
def __init__(self, action, direction, parent, x, y):
self.action = action #akcja jaką ma wykonać (obróc się w lewo, obróć się w prawo, ruch do przodu)
self.direction = direction
self.parent = parent #ojciec wierzchołka
self.x = x
self.y = y
def get_action(self):
return self.action
def set_action(self, action):
self.action = action
def get_direction(self):
return self.direction
def set_direction(self, direction):
self.direction = direction
def get_parent(self):
return self.parent
def set_parent(self, parent):
self.parent = parent
def get_x(self):
return self.x
def set_x(self, x):
self.x = x
def get_y(self):
return self.y
def set_y(self, y):
self.y = y
def cost(map, node): #funkcja kosztu : ile kosztuje przejechanie przez dane pole
return map.get_field_cost(int(node.get_x()), int(node.get_y()))
def heuristic(node, goaltest): #funkcja heurestyki : oszacowuje koszt osiągnięcia stanu końcowego (droga)
return abs(node.get_x() - goaltest[0]) + abs(node.get_y() - goaltest[1])
def f(map, node, goaltest): #funkcja zwracająca sumę funkcji kosztu oraz heurestyki
return cost(map, node) + heuristic(node, goaltest)
# def optimal_goal_test():
def goal_test(elem, goaltest): #funkcja sprawdzająca czy położenie traktora równa się położeniu punktu docelowego, jeśli tak zwraca prawdę, w przeciwnym wypadku fałsz
if elem.get_x() == goaltest[0] and elem.get_y() == goaltest[1]:
return True
else:
return False
def print_moves(elem): #zwraca listę ruchów jakie należy wykonać by dotrzeć do punktu docelowego
moves_list = []
while (elem[0].get_parent() != None):
moves_list.append(elem[0].get_action())
elem = elem[0].get_parent()
moves_list.reverse()
return moves_list
def succ(elem): #funkcja następnika, przypisuje jakie akcje są możliwe do wykonania na danym polu oraz jaki będzie stan (kierunek, położenie) po wykonaniu tej akcji
actions_list = []
temp = copy.copy(elem.get_direction())
if temp == 1:
temp = 4
else:
temp = temp - 1
actions_list.append(("rotate_left", (temp, elem.get_x(), elem.get_y())))
temp = copy.copy(elem.get_direction())
if temp == 4:
temp = 1
else:
temp = temp + 1
actions_list.append(("rotate_right", (temp, elem.get_x(), elem.get_y())))
temp_move_south = elem.get_y() + 1
temp_move_west = elem.get_x() - 1
temp_move_east = elem.get_x() + 1
temp_move_north = elem.get_y() - 1
if tractor.Tractor.is_move_allowed_succ(elem) == "x + 1":
actions_list.append(("move", (elem.get_direction(), temp_move_east, elem.get_y())))
elif tractor.Tractor.is_move_allowed_succ(elem) == "y - 1":
actions_list.append(("move", (elem.get_direction(), elem.get_x(), temp_move_north)))
elif tractor.Tractor.is_move_allowed_succ(elem) == "y + 1":
actions_list.append(("move", (elem.get_direction(), elem.get_x(), temp_move_south)))
elif tractor.Tractor.is_move_allowed_succ(elem) == "x - 1":
actions_list.append(("move", (elem.get_direction(), temp_move_west, elem.get_y())))
return actions_list
def graphsearch(fringe, explored, istate, succ, goaltest, f, map): #przeszukiwanie grafu wszerz
node = Node(None, istate.get_direction(), None, istate.get_x(), istate.get_y()) #wierzchołek początkowy, stworzony ze stanu początkowego traktora
fringe.append((node, 0)) #wierzchołki do odwiedzenia z priorytetem
while True:
if not fringe:
return False
elem = fringe.pop(0) #zdejmujemy wierzchołek z kolejki fringe i rozpatrujemy go
temp = copy.copy(elem[0])
if goal_test(elem[0], goaltest) is True: #jeżeli osiągniemy cel w trakcie przeszukiwania grafu wszerz (wjedziemy na pole docelowe) : zwracamy listę ruchów, po których wykonaniu dotrzemy na miejsce
return print_moves(elem)
explored.append(elem) #dodajemy wierzchołek do listy wierzchołków odwiedzonych
for (action, state) in succ(temp): #iterujemy po wszystkich możliwych akcjach i stanach otrzymanych dla danego wierzchołka grafu
fringe_tuple = []
fringe_tuple_prio = []
explored_tuple = []
for (x, y) in fringe:
fringe_tuple.append((x.get_direction(), x.get_x(), x.get_y()))
fringe_tuple_prio.append(((x.get_direction(), x.get_x(), x.get_y()), y))
for (x, y) in explored:
explored_tuple.append((x.get_direction(), x.get_x(), x.get_y()))
x = Node(action, state[0], elem, state[1], state[2]) #stworzenie nowego wierzchołka, którego rodzicem jest elem
p = f(map, x, goaltest) #liczy priorytet
if state not in fringe_tuple and state not in explored_tuple: #jeżeli stan nie znajduje się na fringe oraz nie znajduje się w liście wierzchołków odwiedzonych
fringe.append((x, p)) #dodanie wierzchołka na fringe
fringe = sorted(fringe, key=itemgetter(1)) #sortowanie fringe'a według priorytetu
elif state in fringe_tuple:
i = 0
for (state_prio, r) in fringe_tuple_prio:
if str(state_prio) == str(state):
if r > p:
fringe.insert(i, (x, p)) #zamiana state, który należy do fringe z priorytetem r na state z priorytetem p (niższym)
fringe = sorted(fringe, key=itemgetter(1)) #sortowanie fringe'a według priorytetu
break
i = i + 1

26
map.py
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@ -23,6 +23,32 @@ class Map:
temp_field = field.Field(temp_plant, temp_rect, temp_soil) temp_field = field.Field(temp_plant, temp_rect, temp_soil)
temp_map_field.append(temp_field) temp_map_field.append(temp_field)
self.fields.append(temp_map_field) self.fields.append(temp_map_field)
def get_field_cost(self, x, y): #zwraca koszt danego pola
field = self.fields[x][y]
if field.get_plant().get_name() == "station" and field.get_plant().get_state() == -1:
return 5
elif field.get_plant().get_name() == "beetroot" and field.get_plant().get_state() > 0 and field.get_plant().get_state() <= 3 * definitions.BEETROOTS_GROW_TIME:
return 10
elif field.get_plant().get_name() == "beetroot" and field.get_plant().get_state() == definitions.BEETROOTS_MAXIMUM_STATE:
return 4
elif field.get_plant().get_name() == "carrot" and field.get_plant().get_state() > 0 and field.get_plant().get_state() <= 3 * definitions.CARROTS_GROW_TIME:
return 10
elif field.get_plant().get_name() == "carrot" and field.get_plant().get_state() == definitions.CARROTS_MAXIMUM_STATE:
return 4
elif field.get_plant().get_name() == "potato" and field.get_plant().get_state() > 0 and field.get_plant().get_state() <= 3 * definitions.POTATOES_GROW_TIME:
return 10
elif field.get_plant().get_name() == "potato" and field.get_plant().get_state() == definitions.POTATOES_MAXIMUM_STATE:
return 4
elif field.get_plant().get_name() == "wheat" and field.get_plant().get_state() > 0 and field.get_plant().get_state() <= 7 * definitions.WHEAT_GROW_TIME:
return 10
elif field.get_plant().get_name() == "wheat" and field.get_plant().get_state() == definitions.WHEAT_MAXIMUM_STATE:
return 4
elif field.get_soil().get_state() is False:
return 2
elif field.get_soil().get_state() is True and field.get_soil().get_water_level() is False:
return 3
elif field.get_soil().get_state() is True and field.get_soil().get_water_level() is True:
return 1
def fill_map(self): #wypełnia mapę teksturami na podstawie logicznego stanu pól def fill_map(self): #wypełnia mapę teksturami na podstawie logicznego stanu pól
for i in range(definitions.WIDTH_AMOUNT): for i in range(definitions.WIDTH_AMOUNT):
for j in range(definitions.HEIGHT_AMOUNT): for j in range(definitions.HEIGHT_AMOUNT):

4
py.py
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@ -1,3 +1,4 @@
import astar
import definitions import definitions
import graph import graph
import map import map
@ -27,7 +28,8 @@ def main():
map1.draw_window(tractor1, tractor1_rect) map1.draw_window(tractor1, tractor1_rect)
if not move_list and plant.Plant.if_any_mature_plant(map1) is True: #jeżeli są jakieś ruchy do wykonania w move_list oraz istnieje jakaś dojrzała roślina if not move_list and plant.Plant.if_any_mature_plant(map1) is True: #jeżeli są jakieś ruchy do wykonania w move_list oraz istnieje jakaś dojrzała roślina
istate = graph.Istate(tractor1.get_direction(), tractor1.get_x() / definitions.BLOCK_SIZE, tractor1.get_y() / definitions.BLOCK_SIZE) #stan początkowy traktora (jego orientacja oraz jego aktualne współrzędne) istate = graph.Istate(tractor1.get_direction(), tractor1.get_x() / definitions.BLOCK_SIZE, tractor1.get_y() / definitions.BLOCK_SIZE) #stan początkowy traktora (jego orientacja oraz jego aktualne współrzędne)
move_list = (graph.graphsearch([], [], istate, graph.succ, plant.Plant.get_closest_mature_plant(map1, tractor1))) #lista z ruchami, które należy po kolei wykonać #move_list = (graph.graphsearch([], [], istate, graph.succ, plant.Plant.get_closest_mature_plant(map1, tractor1))) #lista z ruchami, które należy po kolei wykonać, graph
move_list = (astar.graphsearch([], [], istate, graph.succ, plant.Plant.get_closest_mature_plant(map1, tractor1), astar.f, map1)) #lista z ruchami, które należy po kolei wykonać, astar
elif move_list: #jeżeli move_list nie jest pusta elif move_list: #jeżeli move_list nie jest pusta
tractor1.handle_movement(move_list.pop(0), tractor1_rect) #wykonaj kolejny ruch oraz zdejmij ten ruch z początku listy tractor1.handle_movement(move_list.pop(0), tractor1_rect) #wykonaj kolejny ruch oraz zdejmij ten ruch z początku listy
else: else: