#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