#simName = util.randomString(20);
fitness = evalInd(net,simulator,ind);
ind.getFitness().set(fitness);
print 'Ind: '+repr(ea.actualOne())+' AVG Speed is: '+repr(fitness) +' fitness is: '+repr(ind.getFitness().get());
# evaluated the last individual in the generatio? write stats
if (ea.actualOne() == (popsize-1)):
print 'check: '+repr(ea.generation())
fit = ea.getBestInd().getFitness().get();
er = ea.getBestInd().getFitness().getError();
print '%d %.5f %.5f\n' % (ea.generation(),fit,er)
f.write('%d %.8f %.8f\n' % (ea.generation(),fit,er))
f.flush()
os.fsync(f.fileno()) # just write it to disk
sx.save(ea.generation(),fit,ea.getIndNo(ea.getBest()).m.getVector())
# poc++ and check end of ea
ea.nextIndividual();
f.close()
# load the best one found
ind = ea.getIndNo(ea.getBest());
#net = buildExperiment(ind);
print 'best fitness is: ' +repr(ind.getFitness().get());
# get wa,b,c from ind genome
wa = ind.m.getRange(0,16);
wb = ind.m.getRange(16,25);
wc = ind.m.getRange(25,29);
if (ea.actualOne() == (popsize - 1)):
print 'check: ' + repr(ea.generation())
fit = ea.getBestInd().getFitness().get()
er = ea.getBestInd().getFitness().getError()
print '%d %.5f %.5f\n' % (ea.generation(), fit, er)
f.write('%d %.8f %.8f\n' % (ea.generation(), fit, er))
f.flush()
os.fsync(f.fileno()) # just write it to disk
# poc++ and check end of ea
ea.nextIndividual()
f.close()
# load the best one found
ind = ea.getIndNo(ea.getBest())
#net = buildExperiment(ind);
print 'best fitness is:'
print ind.getFitness().get()
print 'build done writing matrix to file named: \n\n'
file = open('data/ea_%d_architecture.txt' % expNo, 'w')
m = ind.m.getVector()
file.write(str(m))
file.close()
print 'architecture weights written, openning architecture'
# get wa,b,c from ind genome
wa = ind.m.getRange(0, 16)
fitness = evalInd(net, simulator, ind)
ind.getFitness().set(fitness)
print 'Ind: ' + repr(ea.actualOne()) + ' AVG Speed is: ' + repr(
fitness) + ' fitness is: ' + repr(ind.getFitness().get())
# evaluated the last individual in the generatio? write stats
if (ea.actualOne() == (popsize - 1)):
print 'check: ' + repr(ea.generation())
fit = ea.getBestInd().getFitness().get()
er = ea.getBestInd().getFitness().getError()
print '%d %.5f %.5f\n' % (ea.generation(), fit, er)
f.write('%d %.8f %.8f\n' % (ea.generation(), fit, er))
f.flush()
os.fsync(f.fileno()) # just write it to disk
sx.save(ea.generation(), fit, ea.getIndNo(ea.getBest()).m.getVector())
# poc++ and check end of ea
ea.nextIndividual()
f.close()
# load the best one found
ind = ea.getIndNo(ea.getBest())
#net = buildExperiment(ind);
print 'best fitness is: ' + repr(ind.getFitness().get())
# get wa,b,c from ind genome
wa = ind.m.getRange(0, 16)
wb = ind.m.getRange(16, 25)
wc = ind.m.getRange(25, 29)
if (ea.actualOne() == (popsize-1)):
print 'check: '+repr(ea.generation())
fit = ea.getBestInd().getFitness().get();
er = ea.getBestInd().getFitness().getError();
print '%d %.5f %.5f\n' % (ea.generation(),fit,er)
f.write('%d %.8f %.8f\n' % (ea.generation(),fit,er))
f.flush()
os.fsync(f.fileno()) # just write it to disk
# poc++ and check end of ea
ea.nextIndividual();
f.close()
# load the best one found
ind = ea.getIndNo(ea.getBest());
#net = buildExperiment(ind);
print 'best fitness is:'
print ind.getFitness().get();
print 'build done writing matrix to file named: \n\n'
file = open('data/ea_%d_architecture.txt'%expNo, 'w');
m = ind.m.getVector();
file.write(str(m));
file.close();
print 'architecture weights written, openning architecture'
# get wa,b,c from ind genome
