filename = 'prosperities.txt'
# now run the EA, store the course of the prosperity (per time step) only for the first one (best one)
while (ea.wantsEval()):
if (prevgen != ea.generation()):
prevgen = ea.generation()
f = file(filename, 'a+')
f.write('%1.1f %1.6f %s\n' %
((prevgen - 1), ea.getBestInd().getFitness().getValue(),
' '.join(map(str,
ea.getBestInd().getGenome().getVector()))))
f.close()
ind = ea.getCurrentInd()
indNo = ea.currentOne()
val = ind.getGenome().getVector()
name = base + "g" + str(ea.generation()) + "_i" + str(
ea.currentOne()) # set the name (for file storing)
prosp = evalConfiguration(val[0], val[1], val[2], QLambda.DEF_IMPORTANCE,
t, dt, name, indNo) # eval
print '----------------- exp named: ' + name + ' done, the value is ' + str(
prosp[0])
ind.getFitness().setValue(prosp[0])
# set the fitness
ea.nextIndividual()
# continue
# Should be something about 2-3000
name = 'x'
indNo=0
# build the model with default values
net = buildSimulation(QLambda.DEF_ALPHA,QLambda.DEF_GAMMA,QLambda.DEF_LAMBDA,QLambda.DEF_IMPORTANCE,name,indNo)
rl = net.get("RL_QLambda")
importanceIn.setFunctions([ConstantFunction(1,0.5)]) # TODO find some optimal value
# now run the EA (change the models parameters), store the course of the prosperity (per time step) only for the first one (best one)
while(ea.wantsEval()):
alphaIn.setFunctions([ConstantFunction(1,11)])
evaluated = evaluated+1
print "----------------------------------- gen: "+str(ea.generation())+" ind: "+str(ea.currentOne())+ "------------ evaluated "+str(evaluated)
if(ea.currentOne()==2): # TODO delete this
break;
if(prevgen!=ea.generation()):
prevgen=ea.generation()
f=file(filename,'a+')
f.write('%1.1f %1.6f %s\n'%((prevgen-1),ea.getBestInd().getFitness().getValue(),' '.join(map(str, ea.getBestInd().getGenome().getVector()))))
f.close()
ind = ea.getCurrentInd();
indNo = ea.currentOne();
val = ind.getGenome().getVector();
net.reset()
prevgen=0
filename = 'prosperities.txt'
# now run the EA, store the course of the prosperity (per time step) only for the first one (best one)
while(ea.wantsEval()):
if(prevgen!=ea.generation()):
prevgen=ea.generation()
f=file(filename,'a+')
f.write('%1.1f %1.6f %s\n'%((prevgen-1),ea.getBestInd().getFitness().getValue(),' '.join(map(str, ea.getBestInd().getGenome().getVector()))))
f.close()
ind = ea.getCurrentInd();
indNo = ea.currentOne();
val = ind.getGenome().getVector();
name = base+"g"+str(ea.generation())+"_i"+str(ea.currentOne()) # set the name (for file storing)
prosp = evalConfiguration(val[0],val[1],val[2],QLambda.DEF_IMPORTANCE,t,dt,name,indNo) # eval
print '----------------- exp named: '+name+' done, the value is '+str(prosp[0])
ind.getFitness().setValue(prosp[0]); # set the fitness
ea.nextIndividual(); # continue
# Should be something about 2-3000
fitness = ea.getBestInd().getFitness().getValue();
print "==== The result is: "+ea.getBestInd().toString()
prevgen=0
filename = 'prosperities.txt'
# now run the EA, store the course of the prosperity (per time step) only for the first one (best one)
while(ea.wantsEval()):
if(prevgen!=ea.generation()):
prevgen=ea.generation()
f=file(filename,'a+')
f.write('%1.1f %1.6f %s\n'%((prevgen-1),ea.getBestInd().getFitness().getValue(),' '.join(map(str, ea.getBestInd().getGenome().getVector()))))
f.close()
ind = ea.getCurrentInd();
indNo = ea.currentOne();
val = ind.getGenome().getVector();
name = base+"g"+str(ea.generation())+"_i"+str(ea.currentOne()) # set the name (for file storing)
prosp = evalConfiguration(val[0],val[1],val[2],QLambda.DEF_IMPORTANCE,t,dt,name,indNo) # eval
print '----------------- exp named: '+name+' done, the value is '+str(prosp[0])
ind.getFitness().setValue(prosp[0]); # set the fitness
ea.nextIndividual(); # continue
# Should be something about 2-3000
fitness = ea.getBestInd().getFitness().getValue();
print "==== The result is: "+ea.getBestInd().toString()
# run the experiment several times, plot average in the matlab
maxw = 1 # range of all parameters
ea = RealVectorEA(genomelen, False, maxGens, popSize, minw, maxw);
ea.mutate.setStdev(stDev);
ea.setProbabilities(pMut, pCross);
prevgen=0
filename = 'prosperities.txt'
evaluated = 0
# now run the EA, store the course of the prosperity (per time step) only for the first one (best one)
while(ea.wantsEval()):
evaluated = evaluated+1
print "----------------------------------- gen: "+str(ea.generation())+" ind: "+str(ea.currentOne())+ "------------ evaluated "+str(evaluated)
if(prevgen!=ea.generation()):
prevgen=ea.generation()
f=file(filename,'a+')
f.write('%1.1f %1.6f %s\n'%((prevgen-1),ea.getBestInd().getFitness().getValue(),' '.join(map(str, ea.getBestInd().getGenome().getVector()))))
f.close()
ind = ea.getCurrentInd();
indNo = ea.currentOne();
val = ind.getGenome().getVector();
name = base+"g"+str(ea.generation())+"_i"+str(ea.currentOne()) # set the name (for file storing)
prosp = evalConfiguration(val[0],val[1],val[2],QLambda.DEF_IMPORTANCE,t,dt,name,indNo) # eval
print '----------------- exp named: '+name+' done, the value is '+str(prosp[0])
