private CPopulationFitness calculateSimPopulationFitness(CPopulationInfo populationInfo)
{
try
{
ProtocolManager.Open();
Console.WriteLine("Evaluating generation " + populationInfo.Generation);
return(ProtocolManager.Client.calculateSimPopulationFitness(populationInfo));
}
catch (Exception exception)
{
Console.WriteLine("Lost connection to evaluator (" + exception.StackTrace + ")");
Console.WriteLine("Sleeping for 2 seconds, creating new connection.");
ProtocolManager.Close();
Thread.Sleep(2000);
return(calculateSimPopulationFitness(populationInfo));
}
}
public List <FitnessInfo> Evaluate(List <FastCyclicNetwork> phenomes)
{
var populationInfo = new CPopulationInfo
{
Phenomes = FastCyclicNetworkAdapter.Convert(phenomes),
Generation = (int)_ea.CurrentGeneration
};
ProtocolManager.Open();
var fitnessInfo = ProtocolManager.Client.calculateSixMultiplexerPopulationFitness(populationInfo);
EvaluationCount += (uint)fitnessInfo.EvaluationCount;
var result = new List <FitnessInfo>(fitnessInfo.FitnessInfos.Count);
for (var i = 0; i < fitnessInfo.FitnessInfos.Count; i++)
{
var fi = fitnessInfo.FitnessInfos[i];
StopConditionSatisfied |= fi.StopConditionSatisfied;
// Verify that the stop condition is actually really satisfied; if not, there is an error in the Java evaluator and we throw an exception
if (fi.StopConditionSatisfied)
{
var sharpneatFitness = _binarySixMultiplexerEvaluator.Evaluate(phenomes[i]);
var reallySatisfied = sharpneatFitness._fitness >= 1000;
if (!reallySatisfied)
{
Console.Out.WriteLine("ERROR: " + sharpneatFitness._fitness + " versus " + fi.Fitness);
throw new Exception("Noes there is an error in my Java code :(");
}
else
{
Console.Out.WriteLine("Yeey, the result is really correct: " + sharpneatFitness._fitness + " versus " + fi.Fitness);
}
}
result.Add(new FitnessInfo(
fi.Fitness,
fi.AuxFitness.Select(aux => new AuxFitnessInfo(aux.Name, aux.Value)).ToArray())
);
}
return(result);
}
public List <FitnessInfo> Evaluate(List <FastCyclicNetwork> phenomes)
{
var populationInfo = new CPopulationInfo
{
Phenomes = FastCyclicNetworkAdapter.Convert(phenomes),
Generation = (int)_ea.CurrentGeneration
};
var fitnessInfo = calculateSimPopulationFitness(populationInfo);
EvaluationCount += (uint)fitnessInfo.EvaluationCount;
var result = new List <FitnessInfo>(fitnessInfo.FitnessInfos.Count);
foreach (var fi in fitnessInfo.FitnessInfos)
{
StopConditionSatisfied |= fi.StopConditionSatisfied;
result.Add(new FitnessInfo(
fi.Fitness,
fi.AuxFitness.Select(aux => new AuxFitnessInfo(aux.Name, aux.Value)).ToArray())
);
}
return(result);
}
