def loadPopForAnalysis(param, pop, caracs):
txtpop = []
with open('population.txt', 'r') as txt:
for l in txt:
txtpop.append(l)
for i in range(len(txtpop)):
if txtpop[i][:4] == 'nom:':
ind = classes.indiv(param, caracs)
ind.nom = int(txtpop[i].split()[1][:-1])
ind.espece = int(txtpop[i].split()[9][:-1])
ind.score = float(txtpop[i].split()[15][:-1])
ind.classement = int(txtpop[i].split()[17])
j = i + 1
while txtpop[j] != '\n':
g = classes.gene()
g.inNode = int(txtpop[j].split()[0][:-1])
g.outNode = int(txtpop[j].split()[1][:-1])
g.weight = float(txtpop[j].split()[2][:-1])
g.active = bool(txtpop[j].split()[3][:-1] == 'True')
g.code = int(txtpop[j].split()[4])
ind.ADN.addGene(g)
j += 1
pop.addIndiv(ind)
def replayPopFromText(param, pop, caracs):
txtpop = []
with open('replay.txt', 'r') as txt:
for l in txt:
txtpop.append(l)
for i in range(len(txtpop)):
if txtpop[i][:4] == 'nom:':
ind = classes.indiv(param, caracs)
ind.ADN.setNbNodeInt(int(txtpop[i].split()[13][:-1]))
j = i + 1
while txtpop[j] != '\n':
g = classes.gene()
g.inNode = int(txtpop[j].split()[0][:-1])
g.outNode = int(txtpop[j].split()[1][:-1])
g.weight = float(txtpop[j].split()[2][:-1])
g.active = bool(txtpop[j].split()[3][:-1] == 'True')
g.code = int(txtpop[j].split()[4])
ind.ADN.addGene(g)
ind.ADN.siInLibre[g.inNode] = False
if g.outNode < ind.ADN.encOffset:
ind.ADN.siOutLibre[g.outNode] = False
else:
ind.ADN.siEncrLibre[g.outNode] = False
j += 1
ind.nom = pop.getProchNom()
pop.addIndiv(ind)
def creerPopulation(param, pop, caracs):
for i in range(param['nbIndiv']):
ind = classes.indiv(param, caracs)
for connexion in range(param['connexInit']):
g = classes.gene()
unique = False
while not unique:
if connexion == 0:
inNode = 0
else:
inNode = random.randrange(param['nbInput'])
outNode = random.randrange(param['nbOutput'])
if pop.arbreGen[inNode][outNode] == 0:
unique = True
elif not ind.ADN.tellSiGene(pop.arbreGen[inNode][outNode]):
unique = True
g.inNode = inNode
g.outNode = outNode
g.weight = random.uniform(-1, 1)
g.active = True
if pop.arbreGen[inNode][outNode] == 0:
pop.setGeneCode(inNode, outNode)
g.code = pop.arbreGen[inNode][outNode]
ind.ADN.addGene(g)
ind.ADN.siInLibre[inNode] = False
ind.ADN.siOutLibre[outNode] = False
ind.nom = pop.getProchNom()
pop.addIndiv(ind)
def siCreationBoucle(param, ind, inNode, outNode, caracs):
mannequin = classes.indiv(param, caracs)
for g in ind.ADN.seqGene:
gmanq = classes.gene()
g.copyTo(gmanq)
mannequin.ADN.addGene(gmanq)
gmanq = classes.gene()
gmanq.inNode = inNode
gmanq.outNode = outNode
gmanq.active = True
mannequin.ADN.addGene(gmanq)
boolCreationBoucle = False
for node in range(param['nbOutput']):
boolCreationBoucle = boolCreationBoucle or\
recSiBoucle(param, mannequin, node, 1)
for encrNode in range(mannequin.ADN.encOffset, mannequin.maxOutputTotal):
boolCreationBoucle = boolCreationBoucle or\
recSiBoucle(param, mannequin, encrNode, 1)
return boolCreationBoucle
def creerPopulationAvecCouches(param, pop, caracs):
for i in range(param['nbIndiv']):
ind = classes.indiv(param, caracs)
for transverse in range(param['transversesInit']):
unique = False
while not unique:
if transverse == 0:
inNode = 0
else:
inNode = random.randrange(param['nbInput'])
outNode = random.randrange(param['nbOutput'])
if pop.arbreGen[inNode][outNode] == 0:
unique = True
elif not ind.ADN.tellSiGene(pop.arbreGen[inNode][outNode]):
unique = True
for couche in range(param['couchesInit']):
g = classes.gene()
g.inNode = inNode
g.outNode = param['nbOutput'] + ind.ADN.nbNodeInt
g.weight = random.uniform(-1, 1)
g.active = True
if pop.arbreGen[g.inNode][g.outNode] == 0:
pop.setGeneCode(g.inNode, g.outNode)
g.code = pop.arbreGen[g.inNode][g.outNode]
ind.ADN.addGene(g)
inNode = param['nbInput'] + ind.ADN.nbNodeInt
ind.ADN.addNodeInt()
g = classes.gene()
g.inNode = inNode
g.outNode = outNode
g.weight = random.uniform(-1, 1)
g.active = True
if pop.arbreGen[g.inNode][g.outNode] == 0:
pop.setGeneCode(g.inNode, g.outNode)
g.code = pop.arbreGen[g.inNode][g.outNode]
ind.ADN.addGene(g)
ind.ADN.siInLibre[inNode] = False
ind.ADN.siOutLibre[outNode] = False
for nvlInput in range(param['inputSupInit']):
mutation.creationInput(pop, ind)
ind.ADN.seqGene[ind.ADN.compteGene() - 1].weight = random.uniform(
-1, 1)
for connexion in range(param['connexInit']):
mutation.creationConnexion(param, pop, ind, caracs)
ind.ADN.seqGene[ind.ADN.compteGene() - 1].weight = random.uniform(
-1, 1)
for encryption in range(param['encrInit']):
mutation.creationEncryption(param, pop, ind, caracs)
ind.ADN.seqGene[ind.ADN.compteGene() - 1].weight = random.uniform(
-1, 1)
for connexion in range(param['connexInit']):
mutation.creationConnexion(param, pop, ind, caracs)
ind.ADN.seqGene[ind.ADN.compteGene() - 1].weight = random.uniform(
-1, 1)
print(i)
#for g in ind.ADN.seqGene:
# print(str(g.inNode) + '; ' + str(g.outNode) + '; ' + str(g.weight) + '; ' + str(g.active) + '; ' + str(g.code))
ind.nom = pop.getProchNom()
pop.addIndiv(ind)
def seedPopFromCore(param, pop, caracs):
txtpop = []
with open('core.txt', 'r') as txt:
for l in txt:
txtpop.append(l)
for i in range(len(txtpop)):
if txtpop[i][:4] == 'nom:':
ind = classes.indiv(param, caracs)
ind.ADN.setNbNodeInt(int(txtpop[i].split()[13][:-1]))
j = i + 1
while txtpop[j] != '\n':
g = classes.gene()
g.inNode = int(txtpop[j].split()[0][:-1])
g.outNode = int(txtpop[j].split()[1][:-1])
g.weight = float(txtpop[j].split()[2][:-1])
g.active = bool(txtpop[j].split()[3][:-1] == 'True')
g.code = int(txtpop[j].split()[4])
if pop.arbreGen[g.inNode][g.outNode] == 0:
pop.arbreGen[g.inNode][g.outNode] = g.code
if g.code > pop.prochCode:
pop.prochCode = g.code
ind.ADN.addGene(g)
ind.ADN.siInLibre[g.inNode] = False
if g.outNode < ind.ADN.encOffset:
ind.ADN.siOutLibre[g.outNode] = False
else:
ind.ADN.siEncrLibre[g.outNode] = False
j += 1
ind.nom = pop.getProchNom()
pop.addIndiv(ind)
for i in range(param['nbIndiv'] - 1):
clone = classes.indiv(param, caracs)
clone.ADN.setNbNodeInt(ind.ADN.nbNodeInt)
for g0 in ind.ADN.seqGene:
g = classes.gene()
g0.copyTo(g)
clone.ADN.addGene(g)
clone.ADN.siInLibre[g.inNode] = False
if g.outNode < clone.ADN.encOffset:
clone.ADN.siOutLibre[g.outNode] = False
else:
clone.ADN.siEncrLibre[g.outNode] = False
for nvlInput in range(param['inputSupInit']):
mutation.creationInput(pop, clone)
for nvlOutput in range(param['outputSupInit']):
mutation.creationOutput(param, pop, clone, caracs)
for connexion in range(param['connexInit']):
mutation.creationConnexion(param, pop, clone, caracs)
for encryption in range(param['encrInit']):
mutation.creationEncryption(param, pop, clone, caracs)
for chgtPoids in range(param['chgtPoidsInit']):
mutation.changementPoids(clone)
clone.nom = pop.getProchNom()
pop.addIndiv(clone)
print(clone.nom)