inteligentny-traktor/astar.py

from operator import itemgetter
import cart
import copy
from classes import Field


class Istate:
    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:
    def __init__(self, action, direction, parent, x, y):
        self.action = action
        self.direction = direction
        self.parent = parent
        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 fieldCost(T,node):
    c = 0
    if T[node.x-1][node.y-1].plantType == 1:
        c =2
    elif T[node.x-1][node.y-1].plantType == 2:
        c =5
    elif T[node.x-1][node.y-1].plantType == 3:
        c =13
    elif T[node.x-1][node.y-1].plantType == 4:
        c =100000
    else:
        c=0

    if T[node.x-1][node.y-1].isWet == 1:
        c = c + 4
    else:
        c=c+1

    return c


def cost(T, node):
    cost = 0

    while (node.get_parent() != None):
        cost = cost + fieldCost(T, node)
        node = node.get_parent()

    return cost


def f(goaltest, map, node):
    return cost(map, node) + heuristic(goaltest, node)


def goal_test(elem,goaltest):
    if elem.get_x() == goaltest[0] and elem.get_y() == goaltest[1]:
        return True
    else:
        return False


def graphsearch(explored, f, fringe, goaltest, istate, map, succ):  # przeszukiwanie grafu wszerz
    node = Node(None, istate.get_direction(), None, istate.get_x(), istate.get_y())
    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[0])
        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[0], state[1], state[2])  # stworzenie nowego wierzchołka, którego rodzicem jest elem
            p = f(goaltest, map, x)  # liczy priorytet
            #print('Koszt =', p)
            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.pop(i + 1)
                            fringe = sorted(fringe, key=itemgetter(1))  # sortowanie fringe'a według priorytetu
                            break
                    i = i + 1


def heuristic(goaltest, node):
    return abs(node.get_x() - goaltest[0]) + abs(node.get_y() - goaltest[1])


def print_moves(elem):
    moves_list = []
    while (elem.get_parent() != None):
        moves_list.append(elem.get_action())
        elem = elem.get_parent()
    moves_list.reverse()
    return moves_list


def succ(elem):
    actions_list = []
    temp = copy.copy(elem.get_direction())

    if temp == 1:
        temp = 4
    else:
        temp = temp - 1

    actions_list.append(("rotate_right", (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_left", (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 cart.Cart.is_move_allowed_succ(elem) == "x + 1":
        actions_list.append(("move", (elem.get_direction(), temp_move_east, elem.get_y())))
    elif cart.Cart.is_move_allowed_succ(elem) == "y + 1":
        actions_list.append(("move", (elem.get_direction(), elem.get_x(), temp_move_north)))
    elif cart.Cart.is_move_allowed_succ(elem) == "y - 1":
        actions_list.append(("move", (elem.get_direction(), elem.get_x(), temp_move_south)))
    elif cart.Cart.is_move_allowed_succ(elem) == "x - 1":
        actions_list.append(("move", (elem.get_direction(), temp_move_west, elem.get_y())))





    return actions_list