Map2023

In [ ]:

from aigyminsper.search.SearchAlgorithms import BuscaProfundidadeIterativa
from aigyminsper.search.SearchAlgorithms import BuscaCustoUniforme
from aigyminsper.search.SearchAlgorithms import BuscaGananciosa
from aigyminsper.search.SearchAlgorithms import BuscaLargura
from aigyminsper.search.Graph import State
import time
import networkx as nx
import csv

from aigyminsper.search.SearchAlgorithms import BuscaProfundidadeIterativa from aigyminsper.search.SearchAlgorithms import BuscaCustoUniforme from aigyminsper.search.SearchAlgorithms import BuscaGananciosa from aigyminsper.search.SearchAlgorithms import BuscaLargura from aigyminsper.search.Graph import State import time import networkx as nx import csv

In [ ]:

class Map(State):

    def __init__(self, city, cost, op, goal):
        self.city = city
        self.cost_value = cost
        self.operator = op
        self.goal = goal
    
    def successors(self):
        sucessors = []
        neighbors = Map.area[self.city]
        for next_city in neighbors:
            sucessors.append(Map(next_city[1], next_city[0], next_city[1], self.goal))
        return sucessors
    
    def is_goal(self):
        return (self.city == self.goal)
    
    def description(self):
        return "Um mapa para procurar"
    
    def cost(self):
        return self.cost_value
    
    def print(self):
        return str(self.operator)
    
    def env(self):
        return self.city
    
    def h(self):
        return int(Map.g.edges[self.city,self.goal]['distance'])
        #return random.randint(1,10)
        #return 1

    @staticmethod
    def createArea():
        Map.area = {
            'a':[(3,'b'),(6,'c')],
            'b':[(3,'a'),(3,'h'),(3,'k')],
            'c':[(6,'a'),(2,'g'),(3,'d'),(2,'o'),(2,'p')],
            'd':[(3,'c'),(1,'f'),(1,'e')],
            'e':[(2,'i'),(1,'f'),(1,'d'),(14,'m')],
            'f':[(1,'g'),(1,'e'),(1,'d')],
            'g':[(2,'c'),(1,'f'),(2,'h')],
            'h':[(2,'i'),(2,'g'),(3,'b'),(4,'k')],
            'i':[(2,'e'),(2,'h')],
            'l':[(1,'k')],
            'k':[(1,'l'),(3,'n'),(4,'h'),(3,'b')],
            'm':[(2,'n'),(1,'x'),(14,'e')],
            'n':[(2,'m'),(3,'k')],
            'o':[(2,'c')],
            'p':[(2,'c')],
            'x':[(1,'m')]
            }
        
    @staticmethod
    def createHeuristics():
        #
        # O arquvo MapHeuristics.csv considera apenas os objetivos "o" e "x"
        # TODO modificar o arquivo para considerar todas as cidades. talvez modificar
        # a estrutura do arquivo considerando uma estrutura otimizada
        #
        Map.g = nx.Graph()
        f = csv.reader(open("data/MapHeuristics.csv","r"))
        for row in f: 
            Map.g.add_edge(row[0],row[1], distance = row[2])

class Map(State): def __init__(self, city, cost, op, goal): self.city = city self.cost_value = cost self.operator = op self.goal = goal def successors(self): sucessors = [] neighbors = Map.area[self.city] for next_city in neighbors: sucessors.append(Map(next_city[1], next_city[0], next_city[1], self.goal)) return sucessors def is_goal(self): return (self.city == self.goal) def description(self): return "Um mapa para procurar" def cost(self): return self.cost_value def print(self): return str(self.operator) def env(self): return self.city def h(self): return int(Map.g.edges[self.city,self.goal]['distance']) #return random.randint(1,10) #return 1 @staticmethod def createArea(): Map.area = { 'a':[(3,'b'),(6,'c')], 'b':[(3,'a'),(3,'h'),(3,'k')], 'c':[(6,'a'),(2,'g'),(3,'d'),(2,'o'),(2,'p')], 'd':[(3,'c'),(1,'f'),(1,'e')], 'e':[(2,'i'),(1,'f'),(1,'d'),(14,'m')], 'f':[(1,'g'),(1,'e'),(1,'d')], 'g':[(2,'c'),(1,'f'),(2,'h')], 'h':[(2,'i'),(2,'g'),(3,'b'),(4,'k')], 'i':[(2,'e'),(2,'h')], 'l':[(1,'k')], 'k':[(1,'l'),(3,'n'),(4,'h'),(3,'b')], 'm':[(2,'n'),(1,'x'),(14,'e')], 'n':[(2,'m'),(3,'k')], 'o':[(2,'c')], 'p':[(2,'c')], 'x':[(1,'m')] } @staticmethod def createHeuristics(): # # O arquvo MapHeuristics.csv considera apenas os objetivos "o" e "x" # TODO modificar o arquivo para considerar todas as cidades. talvez modificar # a estrutura do arquivo considerando uma estrutura otimizada # Map.g = nx.Graph() f = csv.reader(open("data/MapHeuristics.csv","r")) for row in f: Map.g.add_edge(row[0],row[1], distance = row[2])

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def main():

    Map.createArea()
    Map.createHeuristics()

    #state = Map('i', 0, 'i', 'o')
    state = Map('b', 0, 'b', 'o')
    #state = Map('i', 0, 'i', 'x')
    #algorithm = BuscaLargura()
    #algorithm = BuscaCustoUniforme()
    algorithm = BuscaGananciosa()
    ts = time.time()
    result = algorithm.search(state, trace=True)
    tf = time.time()
    if result != None:
        print(result.show_path())
    else:
        print('Nao achou solucao')
    print('Tempo de processamento em segundos: ' + str(tf-ts))
    print('O custo da solucao eh: '+str(result.g))

def main(): Map.createArea() Map.createHeuristics() #state = Map('i', 0, 'i', 'o') state = Map('b', 0, 'b', 'o') #state = Map('i', 0, 'i', 'x') #algorithm = BuscaLargura() #algorithm = BuscaCustoUniforme() algorithm = BuscaGananciosa() ts = time.time() result = algorithm.search(state, trace=True) tf = time.time() if result != None: print(result.show_path()) else: print('Nao achou solucao') print('Tempo de processamento em segundos: ' + str(tf-ts)) print('O custo da solucao eh: '+str(result.g))

In [ ]:

if __name__ == '__main__':
    main()

if __name__ == '__main__': main()