示例#1
0
def init():
    drop()
    print'Initializing...'
    str=GeneStructure(gsNew=-1,fromDB=1,num=0)
    g=Gene(structure=str,weights=[],thresholds=[],num=0)
    for i in range (0,SIZE_SENSOR+SIZE_OUTPUT+1):
        str.appendNeuron()
        g.thresholds.append(random.uniform(-0.5,0.5))
    for i in range(0,SIZE_SENSOR):
        str.appendSynapse(origin=i,terminus=SIZE_SENSOR+SIZE_OUTPUT)
        g.weights.append(random.uniform(-2,2))
        str.appendSynapse(origin=SIZE_SENSOR+SIZE_OUTPUT,terminus=i+SIZE_SENSOR)
        g.weights.append(random.uniform(-2,2))
    save.saveStruct(str.pack())
    g.set()
    sp1=Specie(members=[g],appearTime=0)
    nature=Nature(species=[sp1],generation=0,restResource=0)
    save.saveCurrent(nature.packCurrent())
    print'Initializing has been done.'
示例#2
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文件: specie.py 项目: hdl730/atlantis
 def breed(self):
     if len(self.genes)>7:
         r=[i for i in (1,WHO_MATE) if i<len(self.genes)]
         for i in range(0,SPEED_MATE):
             wife=choice(r)
             new1=mate(gene1=self.genes[0],gene2=self.genes[wife])
             self.newGenesList.append(new1)
             self.genes.append(new1)
     if len(self.genes)>5:
         t=choice(self.genes)
         new2=Gene(structure=t.structure,weights=t.weights,thresholds=t.thresholds)
         new3=Gene(structure=t.structure,weights=t.weights,thresholds=t.thresholds)
         new2.addNRand()
         self.newSpiecesList.append(new2)
         for n in new3.getSRand(sizeO=SIZE_OUTPUT,sizeS=SIZE_SENSOR):
             self.newSpiecesList.append(n)
     for i in range(0,SPEED_MUTATION):
         tmp=choice(self.genes)
         new1=Gene(structure=tmp.structure,weights=tmp.weights,thresholds=tmp.thresholds)
         new1.mutation()
         self.newGenesList.append(new1)
         self.genes.append(new1)
示例#3
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 def breed(self):
     if len(self.genes) > 7:
         r = [i for i in (1, WHO_MATE) if i < len(self.genes)]
         for i in range(0, SPEED_MATE):
             wife = choice(r)
             new1 = mate(gene1=self.genes[0], gene2=self.genes[wife])
             self.newGenesList.append(new1)
             self.genes.append(new1)
     if len(self.genes) > 5:
         t = choice(self.genes)
         new2 = Gene(structure=t.structure,
                     weights=t.weights,
                     thresholds=t.thresholds)
         new3 = Gene(structure=t.structure,
                     weights=t.weights,
                     thresholds=t.thresholds)
         new2.addNRand()
         self.newSpiecesList.append(new2)
         for n in new3.getSRand(sizeO=SIZE_OUTPUT, sizeS=SIZE_SENSOR):
             self.newSpiecesList.append(n)
     for i in range(0, SPEED_MUTATION):
         tmp = choice(self.genes)
         new1 = Gene(structure=tmp.structure,
                     weights=tmp.weights,
                     thresholds=tmp.thresholds)
         new1.mutation()
         self.newGenesList.append(new1)
         self.genes.append(new1)
示例#4
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    def debug(self):
        print 'Infos of \'this\' unit:'
        print 'Neurons:'
        for i in range(0,len(self.neurons)):
            print 'No.',i,':'
            self.neurons[i].debug()
        print 'Gene:'
        self.gene.debug()

if __name__=='__main__':
    from gene.gene import Gene
    from gene.genestructure import GeneStructure
    import random
    str=GeneStructure(gsNew=-1)
    g=Gene(structure=str,weights=[],thresholds=[])
    for i in range (0,60):
        str.appendNeuron()
        g.thresholds.append(random.uniform(-0.5,0.5))
    for i in range(0,20):
        for j in range(20,40):
            str.appendSynapse(origin=i,terminus=j)
            str.appendSynapse(origin=j,terminus=i+40)
            g.weights.append(random.uniform(-2,2))
            g.weights.append(random.uniform(-2,2))
    # str.appendSynapse(origin=0,terminus=4)
    # str.appendSynapse(origin=0,terminus=5)
    # str.appendSynapse(origin=1,terminus=5)
    # str.appendSynapse(origin=4,terminus=3)
    # str.appendSynapse(origin=4,terminus=2)
    # str.appendSynapse(origin=5,terminus=2)
示例#5
0
    structure = GeneStructure(gsNew=-1,
                              fromDB=1,
                              num=num,
                              neurons=neurons,
                              sizeS=size)
    members = []
    for g in genes:
        curGene = geneBase.find({'_id': g})[0]
        weights = curGene['weights']
        thresholds = curGene['thresholds']
        fitness = curGene['fitness']
        record = {int(k): v for k, v in dict(curGene['record']).items()}
        num = curGene['_id']
        gene = Gene(structure=structure,
                    weights=weights,
                    thresholds=thresholds,
                    fitness=fitness,
                    record=record,
                    num=num)
        members.append(gene)
    spicie = Specie(members=members, appearTime=appear)
    spicieList.append(spicie)

nature = Nature(species=spicieList,
                generation=generation,
                restResource=restRes)

for i in range(0, MAX_GENERATION_PER):
    nature.loop()

save.saveCurrent(nature.packCurrent())