示例#1
0
ii = 0;

INdim = 2;
OUTdim = 1;
N = 1;
minw = 0;
maxw = 0.3;
popsize = 1;
maxgen = 0;

t = 5;
dt = 0.001;

# init EA
ea = EA(INdim, OUTdim, N, maxgen,popsize,minw,maxw);
ea.initPop();

# evolution insert here
while ea.wantsEval():
    print 'gen: '+repr(ea.generation())+' actual ind is ' +repr(ea.actualOne())

    ind = ea.getInd();
    ind.printMatrix();        
    
    error = evalInd(ind);
    #error = 0;
    print 'Ind: '+repr(ea.actualOne())+' Error is: '+repr(error) +' fitness is: '+repr(ind.getFitness().get());
    
    # poc++ and check end of ea
    ea.nextIndividual();
示例#2
0

# setup
INdim = 2
OUTdim = 1
N = 5
minw = -1
maxw = 1
popsize = 5
maxgen = 1

t = 5
dt = 0.001

ea = EA(INdim, OUTdim, N, maxgen, popsize, minw, maxw)
ea.initPop()

while ea.wantsEval():
    print ea.actualOne()

    ind = ea.getInd()
    ind.printMatrix()

    # pass weights as python methods
    def getI1(w):
        w = ind.getMatrix().get2DInMatrixNo(0)
        return w

    def getI2(w):
        w = ind.getMatrix().get2DInMatrixNo(1)
        return w
示例#3
0
文件: 1annea.py 项目: jvitku/designer
else: 
    useRecurrent =False
    pMut = 0.6;
    pCross = 1;
    N=5
    popsize = 4;
    maxgen = 10;

numRuns=10;
for expNo in range(numRuns):

    print '----------------------- experiment number %d'%expNo
    # init EA
    ea = EA(INdim, OUTdim, N, maxgen,popsize,minw,maxw);
    ea.setProbabilities(pMut,pCross);
    ea.initPop();
    f = open('data/ea_%d.txt'%expNo, 'w');

    # evolution insert here
    while ea.wantsEval():
        print 'Gen: '+repr(ea.generation())+'/'+repr(maxgen)+' actual ind is ' +repr(ea.actualOne())+'/'+repr(popsize)+' best so far: '+repr(ea.getBestFitness());
        
        ind = ea.getInd();
        #ind.printMatrix();        
    
        error = evalInd(ind);
        ind.getFitness().setError(error);
    
        print 'Ind: '+repr(ea.actualOne())+' Error is: '+repr(error) +' fitness is: '+repr(ind.getFitness().get());
    
        print ea.getActualWeights();
示例#4
0
    popsize = 30
    maxgen = 100
    N = 4

else:
    useRecurrent = False
    pMut = 0.6
    pCross = 1
    N = 5
    popsize = 4
    maxgen = 5

# init EA
ea = EA(INdim, OUTdim, N, maxgen, popsize, minw, maxw)
ea.setProbabilities(pMut, pCross)
ea.initPop()
expNo = round(1000000 * random.random(), 0)
# generate some number for text file data
print expNo
f = open('data/ea_%d.txt' % expNo, 'w')

# evolution insert here
while ea.wantsEval():
    print 'Gen: ' + repr(
        ea.generation()) + '/' + repr(maxgen) + ' actual ind is ' + repr(
            ea.actualOne()) + '/' + repr(popsize) + ' best so far: ' + repr(
                ea.getBestFitness())

    ind = ea.getInd()
    #ind.printMatrix();