def setUp(self):
self.n = {
'a': Noeud(0, 0, 'a'),
'b': Noeud(0, 1, 'b'),
'c': Noeud(1, 0, 'c'),
'd': Noeud(-1, 0, 'd'),
'e': Noeud(0, -1, 'e'),
}
self.g1 = Graphe(
[self.n['a'], self.n['b'], self.n['c'], self.n['d'], self.n['e']],
[(self.n['a'], self.n['b'], 1), (self.n['a'], self.n['c'], 1),
(self.n['a'], self.n['d'], 1)])
def Aetoil(initRow, initCol, endRow, endCol, wallStates):
noeudInitial = Noeud(([initRow,initCol]), 0, None)
goalStates = [endRow,endCol]
frontiere = [(noeudInitial.cost + manhattan(noeudInitial.position, goalStates), noeudInitial)]
reserve = {}
noeudCourant = noeudInitial
while frontiere != [] and not noeudCourant.position == goalStates:
(min_f, noeudCourant) = heapq.heappop(frontiere)
if noeudCourant.position == goalStates:
break
next_row = noeudCourant.position[0]
next_col = noeudCourant.position[1]
if ((next_row,
next_col) not in wallStates) and next_row >= 0 and next_row < game.spriteBuilder.rowsize and next_col > 0 and next_col < game.spriteBuilder.colsize:
if noeudCourant.identifiantNoeud() not in reserve:
reserve[noeudCourant.identifiantNoeud()] = noeudCourant.cost
nouveauxNoeuds = noeudCourant.expand()
for noeud in nouveauxNoeuds:
f = noeud.cost + manhattan(noeud.position, goalStates)
heapq.heappush(frontiere, (f, noeud))
return noeudCourant
def test_distance(self):
n1 = Noeud(0, 0, "1")
n2 = Noeud(0, 1, "2")
n3 = Noeud(1, 0, "3")
n4 = Noeud(1, 1, "4")
self.assertEqual(n1.distance(n2), 1)
self.assertEqual(n1.distance(n3), 1)
self.assertEqual(n1.distance(n4), sqrt(2))
def __init__(self, length, nb_e, nb_s):
self.length = length
self.contenu = [Individu(nb_e,nb_s, i) for i in range(length)]
self.oldGen = []
self.nb_e = nb_e
self.nb_s = nb_s
self.noeuds = [Noeud(i, "entree") for i in range(nb_e)]
self.noeuds.extend([Noeud(i,"sortie") for i in range(nb_e, nb_e + nb_s)])
self.generationCount = 0
self.indiceInnovation = 0
self.lastIndId = length
self.lastEspId = 0
self.averageFitness = None
self.averageRawFitness = None
self.historique = []
self.especes = []
self.histEspeces = []
self.bestDisplay = 10
self.best = []
# self.especesFig, self.especesAx = plt.subplots(figsize=(20, 20*500/860))
"""Cette liste contiendra les différentes opérations génétiques structurelles
def main():
# création de la chaine
liste = Liste_Doublement_Chainee()
for i in range(5):
n = Noeud()
n.cle = i
liste.add_noeud_fin(n)
# déclaration et affectation des variables
moyenne = 0.0
fini_en_moins_de_trois = 0.0
nb_iterations = 100000
# boucle qui permet de répéter les test pendant "nb_iterations"
for i in range(nb_iterations):
# Sélection aléatoire du noeud de départ
noeud_markov = liste.get_noeud(random.randint(1, 3))
compteur = 0
# boucle qui effectue le test de deplacement aléatoire jusqu'a se retrouver dans un état absorbant
while True:
noeud_markov = deplacement_aleatoire(noeud_markov)
compteur = compteur + 1
# état absorbant
if noeud_markov.suivant is None or noeud_markov.precedent is None:
break
# évaluation du moment ou le test prends fin
if compteur == 1 or compteur == 2:
fini_en_moins_de_trois = fini_en_moins_de_trois + 1
moyenne = moyenne + compteur
# affichage des statistiques des tests effectués
moyenne = moyenne / nb_iterations
print "moyenne:", moyenne
print "pourcentage qui ont finis apres trois pas ou plus:", (1 - (
fini_en_moins_de_trois / nb_iterations)) * 100, "%"
def create_graph(graph_id, path_file):
with open(path_file, newline='') as csv_file:
reader = csv.reader(csv_file, delimiter='\t')
Graphe1 = GrapheOriente(graph_id)
nb_node = next(reader)
for i in range(1, int(nb_node[0]) + 1):
Graphe1.ajouterNoeud(Noeud(i))
for row in reader:
Graphe1.ajouterLien(Lien(int(row[0]), int(row[1]), float(row[2])))
return Graphe1
def mutationNoeud(self, ind):
con = ut.randomPick(list(ind.genome.connexions.values()))
while ind.estRecursive(con):
con = ut.randomPick(list(ind.genome.connexions.values()))
idNouvNoeud = len(self.noeuds)
for i in range(self.indiceInnovation):
t1, e1, s1 = self.historique[i]
if t1 == 1:
t2, e2, s2 = self.historique[i+1]
if e1 == con.entree and s2 == con.sortie and (s1 not in ind.idToPos):
ind.insertNoeud(con, 1, con.poids, i, s1)
break
else:
ind.insertNoeud(con, 1, con.poids, self.indiceInnovation, idNouvNoeud)
self.historique.append((1,con.entree,idNouvNoeud))
self.historique.append((2,idNouvNoeud,con.sortie))
self.noeuds.append(Noeud(idNouvNoeud, "cachee"))
self.indiceInnovation += 2
def test_eq(self):
n1 = Noeud(1, 2, "blah")
n2 = Noeud(1, 2, "blah")
n3 = Noeud(1, 2, "lah")
n4 = Noeud(1, 3, "blah")
n5 = Noeud(2, 2, "blah")
n6 = Noeud(2, 3, "lah")
self.assertEqual(n1, n2)
self.assertFalse(n1 == n3)
self.assertFalse(n1 == n4)
self.assertFalse(n1 == n5)
self.assertFalse(n1 == n6)
def setUp(self):
self.n = {
'a': Noeud(0, 0, 'a'),
'b': Noeud(0, 2, 'b'),
'c': Noeud(2, 2, 'c'),
'd': Noeud(3, 4, 'd'),
'e': Noeud(4, 2, 'e'),
'f': Noeud(4, 4, 'f'),
}
self.g1 = Graphe([
self.n['a'], self.n['b'], self.n['c'], self.n['d'], self.n['e'],
self.n['f']
], [(self.n['a'], self.n['b'], self.n['a'].distance(self.n['b'])),
(self.n['a'], self.n['c'], self.n['a'].distance(self.n['c'])),
(self.n['b'], self.n['d'], self.n['b'].distance(self.n['d'])),
(self.n['d'], self.n['f'], self.n['d'].distance(self.n['f'])),
(self.n['c'], self.n['d'], self.n['c'].distance(self.n['d'])),
(self.n['c'], self.n['e'], self.n['c'].distance(self.n['e'])),
(self.n['e'], self.n['f'], self.n['e'].distance(self.n['f']))])
def main():
#for arg in sys.argv:
iterations = 100 # default
if len(sys.argv) == 2:
iterations = int(sys.argv[1])
print("Iterations: ")
print(iterations)
init()
#-------------------------------
# Building the matrix
#-------------------------------
# on localise tous les états initiaux (loc du joueur)
initStates = [o.get_rowcol() for o in game.layers['joueur']]
print("Init states:", initStates)
# on localise tous les objets ramassables
goalStates = [o.get_rowcol() for o in game.layers['ramassable']]
print("Goal states:", goalStates)
# on localise tous les murs
wallStates = [w.get_rowcol() for w in game.layers['obstacle']]
#print ("Wall states:", wallStates)
#-------------------------------
# Building the best path with A*
#-------------------------------
noeudInitial = Noeud(list(initStates[0]), 0, None)
frontiere = [
(noeudInitial.cost + manhattan(noeudInitial.position, goalStates[0]),
noeudInitial)
]
reserve = {}
noeudCourant = noeudInitial
while frontiere != [] and not noeudCourant.position == goalStates[0]:
(min_f, noeudCourant) = heapq.heappop(frontiere)
if noeudCourant.position == list(goalStates[0]):
break
next_row = noeudCourant.position[0]
next_col = noeudCourant.position[1]
if (
(next_row, next_col) not in wallStates
) and next_row >= 0 and next_row <= 20 and next_col >= 0 and next_col <= 20:
if noeudCourant.identifiantNoeud() not in reserve:
reserve[noeudCourant.identifiantNoeud()] = noeudCourant.cost
nouveauxNoeuds = noeudCourant.expand()
for noeud in nouveauxNoeuds:
f = noeud.cost + manhattan(noeud.position, goalStates[0])
heapq.heappush(frontiere, (f, noeud))
#-------------------------------
# Moving along the path
#-------------------------------
# bon ici on fait juste un random walker pour exemple...
row, col = initStates[0]
#row2,col2 = (5,5)
"""for i in range(iterations):
x_inc,y_inc = random.choice([(0,1),(0,-1),(1,0),(-1,0)])
next_row = row+x_inc
next_col = col+y_inc
if ((next_row,next_col) not in wallStates) and next_row>=0 and next_row<=20 and next_col>=0 and next_col<=20:
player.set_rowcol(next_row,next_col)
print ("pos 1:",next_row,next_col)
game.mainiteration()
col=next_col
row=next_row
"""
moves = []
while noeudCourant != None:
moves.insert(0, [noeudCourant.position[0], noeudCourant.position[1]])
noeudCourant = noeudCourant.father
for i in moves:
player.set_rowcol(i[0], i[1])
game.mainiteration()
# si on a trouvé l'objet on le ramasse
if (row, col) == goalStates[0]:
o = game.player.ramasse(game.layers)
game.mainiteration()
print("Objet trouvé!", o)
break
'''
#x,y = game.player.get_pos()
'''
pygame.quit()
from noeud import Noeud
from graphe import Graphe
from dfs import DFSSolver
from bfs import BFSSolver
from astar import AStarSolver
# Les villes
villes = {
'Lausanne': Noeud(110, 260, 'Lausanne'),
'Geneve': Noeud(40, 300, 'Geneve'),
'Sion': Noeud(200, 300, 'Sion'),
'Neuchatel': Noeud(150, 170, 'Neuchatel'),
'Bern': Noeud(210, 280, 'Bern'),
'Basel': Noeud(230, 65, 'Basel'),
'Fribourg': Noeud(175, 200, 'Fribourg'),
'Zurich': Noeud(340, 90, 'Zurich'),
'Aarau': Noeud(290, 95, 'Aarau'),
'Luzern': Noeud(320, 155, 'Luzern'),
'St-Gallen': Noeud(85, 455, 'St-Gallen'),
'Thun': Noeud(235, 210, 'Thun'),
}
# Les routes.
routes = [
(villes['Lausanne'], villes['Geneve'], villes['Lausanne'].distance(villes['Geneve'])),
(villes['Sion'], villes['Lausanne'], villes['Sion'].distance(villes['Lausanne'])),
(villes['Neuchatel'], villes['Lausanne'], villes['Neuchatel'].distance(villes['Lausanne'])),
(villes['Fribourg'], villes['Lausanne'], villes['Fribourg'].distance(villes['Lausanne'])),
(villes['Fribourg'], villes['Bern'], villes['Fribourg'].distance(villes['Bern'])),
(villes['Sion'], villes['Thun'], villes['Sion'].distance(villes['Thun'])),
nb_node = next(reader)
for i in range(1, int(nb_node[0]) + 1):
Graphe1.ajouterNoeud(Noeud(i))
for row in reader:
Graphe1.ajouterLien(Lien(int(row[0]), int(row[1]), float(row[2])))
return Graphe1
#def dijkstra(id_node_source, id_node_dest):
# nodes_list = []
noeud1 = Noeud(11)
noeud2 = Noeud(22)
noeud3 = Noeud(33)
noeud4 = Noeud(4444)
lien1 = Lien(11, 22, 10)
lien2 = Lien(22, 33, 11)
lien4 = Lien(11, 4444, 11)
g1 = GrapheOriente(10)
g1.ajouterNoeud(noeud1)
g1.ajouterNoeud(noeud2)
g1.ajouterNoeud(noeud3)
g1.ajouterNoeud(noeud4)
from noeud import Noeud
from graphe import Graphe
from dfs import DFSSolver
from bfs import BFSSolver
from astar import AStarSolver
# les noeuds du graphe
noeuds = {
'A': Noeud(0, 16, 'A'),
'B': Noeud(5, 13, 'B'),
'C': Noeud(0, 10, 'C'),
'D': Noeud(5, 8, 'D'),
'E': Noeud(11, 18, 'E'),
'F': Noeud(15, 13, 'F'),
'G': Noeud(29, 18, 'G'),
'H': Noeud(26, 0, 'H'),
'I': Noeud(12, 10, 'I'),
'J': Noeud(17, 7, 'J'),
'K': Noeud(11, 3, 'K'),
'L': Noeud(22, 16, 'L'),
'M': Noeud(25, 12, 'M'),
'N': Noeud(24, 6, 'N'),
'O': Noeud(20, 0, 'O'),
'P': Noeud(5, 0, 'P'),
}
# les arcs
arcs = [(noeuds['A'], noeuds['B'], noeuds['A'].distance(noeuds['B'])),
(noeuds['A'], noeuds['E'], noeuds['A'].distance(noeuds['E'])),
(noeuds['B'], noeuds['C'], noeuds['B'].distance(noeuds['C'])),
def ajoutLien(self,Lien):
self._dictLiens.append(Lien)
Noeud.ajoutIdentifiantLien(Lien,Lien.getId())
chemin_final = parcours_en_profondeur(grid, grid[0][0], chemin)
return chemin_final
#Construction de la grille graphique
width = 30
height = 30
xvalues = [i for i in range(width)]
yvalues = [j for j in range(height)]
xx, yy = np.meshgrid(xvalues, yvalues)
plt.plot(xx, yy, color='k', linestyle='none')
plt.gca().invert_yaxis()
plt.gca().xaxis.set_ticks_position('top')
#Construction de la grille en terme de noeud
rows = height - 1
cols = width - 1
grid = [[Noeud(i, j) for j in range(cols)] for i in range(rows)]
#Construction du labyrinthe, algorithme de Prim
prim_algorithm(grid, width, height, [], True)
#Update du labyrinthe dans la grille graphique
draw_borders(grid)
#ShowOff
plt.show()
#SolveOff
draw_way_out(trouver_le_chemin(grid), grid)
def ajouterNoeud(self,Noeud):
self._nbrNoeuds+=1
self._dictNoeuds[Noeud.getId()]=Noeud
