コード例 #1
0
ファイル: 2hnnea.py プロジェクト: jvitku/designer
if config == 1: # this works pretty well (approximates sum)
    useRecurrent = True
    pMut = 0.1
    pCross = 0.9;
    popsize = 3;
    maxgen = 1;
elif config ==2:
    useRecurrent = True
    pMut = 0.1
    pCross = 0.9;
    popsize = 5;
    maxgen = 15;

#################
ea = EA(INdim,OUTdim, numIns,numOuts, maxgen,popsize,minw,maxw);
ea.setProbabilities(pMut,pCross);
ea.initPop();
print 'starting build'
# evolution insert here
# 
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();        
コード例 #2
0
ファイル: 5weights.py プロジェクト: jvitku/nengo_1.4
# which setup to use?
config=1

if config == 1: # this works pretty well (approximates sum)
    useRecurrent =True
    pMut = 0.1
    pCross = 0.9;
    popsize = 3;
    maxgen = 1;
    N=2


print N
#################
ea = EA(INdim, OUTdim, N, maxgen,popsize,minw,maxw);
ea.setProbabilities(pMut,pCross);
ea.initPop();
print 'starting build'
# evolution insert here


ind = ea.getInd();
ind.printMatrix();        
net = buildExperiment(ind);
print 'build done \n\n'




コード例 #3
0
if config == 1:  # this works pretty well (approximates sum)
    useRecurrent = True
    pMut = 0.1
    pCross = 0.9
    popsize = 3
    maxgen = 1
elif config == 2:
    useRecurrent = True
    pMut = 0.1
    pCross = 0.9
    popsize = 5
    maxgen = 15

#################
ea = EA(INdim, OUTdim, numIns, numOuts, maxgen, popsize, minw, maxw)
ea.setProbabilities(pMut, pCross)
ea.initPop()
print 'starting build'
# evolution insert here
#
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(