public StatusEventArgs(GeneticResult geneticResult)
{
this.GeneticResult = geneticResult;
}
public void Init(TradeSystem tradeSystem, bool seedSystem, double stopOutValue)
{
Initiated();
this.Proceed = true;
this.workToDo = this.GenerationSize * this.NumberOfIteration;
this.workDone = 0;
this.CurrentIteration = 0;
this.CurrentGeneration = 0;
this.BestResult = null;
List<Chromosome> currentChromosomes;
List<TradeRule> mixedTradeRules;
Chromosome seedChromosome = null;
if (seedSystem)
{
seedChromosome = new Chromosome() { BuyCondition = tradeSystem.BuyCondition, SellCondition = tradeSystem.SellCondition };
}
//if (this.MixedTradeRules == null)
//{
// this.MixedTradeRules = this.MachineLearnerTradeRule.GenerateTradeRuleForGroups(this.PopulationSize);
// this.BuyRules = this.BuyRules.Concat(this.MixedTradeRules).ToList();
// this.SellRules = this.SellRules.Concat(this.MixedTradeRules).ToList();
//}
TradeType? tradeType = null;
if (tradeSystem.Longs && !tradeSystem.Shorts) // long only
{
tradeType = TradeType.longTrade;
}
else if (!tradeSystem.Longs && tradeSystem.Shorts) // short only
{
tradeType = TradeType.shortTrade;
}
for (int i = 1; i <= this.NumberOfIteration; i++)
{
if (!Proceed)
break;
mixedTradeRules = this.MachineLearnerTradeRule.GenerateTradeRuleForGroups(this.PopulationSize);
this.BuyRules = this.BuyRulesCache.Concat(mixedTradeRules).ToList();
this.SellRules = this.SellRulesCache.Concat(mixedTradeRules).ToList();
if (i == 1 && !seedSystem)
{
this.BestResult = null;
}
else if (!this.Seed)
{
this.BestResult = null;
}
this.CurrentIteration = i;
currentChromosomes = new List<Chromosome>();
UpdateProgress(string.Format("Processing Iteration: {0}", i));
if (!Proceed)
break;
for (int g = 1; g <= this.GenerationSize; g++)
{
if (!currentChromosomes.Any())
{
currentChromosomes = GeneratePopulation();
if(seedChromosome != null)
{
currentChromosomes[0] = seedChromosome;
}
}
if (!Proceed)
break;
currentChromosomes = EvaluateFitness(tradeSystem, currentChromosomes, i, g, stopOutValue, tradeType).Select(d => d.Chromosome).Cast<Chromosome>().ToList();
if (this.BestResult != null)
{
ChromosomeProcessed(this.BestResult);
currentChromosomes = Breed(currentChromosomes);
}
this.workDone++;
this.CurrentGeneration = g;
UpdateProgress(string.Format("Completed - Iteration {0}, Generation {1}", i, g));
}
}
Completed();
}
private void ChromosomeProcessed(GeneticResult geneticResult)
{
if (OnChromosomeProcessed == null)
return;
StatusEventArgs args;
args = new StatusEventArgs(geneticResult);
OnChromosomeProcessed(this, args);
}
public List<dynamic> EvaluateFitness(TradeSystem tradeSystem, List<Chromosome> chromosomes, int iteration, int generation, double stopOutValue, TradeType? tradeType = null)
{
List<dynamic> list = new List<dynamic>();
if (chromosomes == null)
return list;
Chromosome bestChromosome = null;
double currentFitnessValue = 0D;
double bestFitnessValue = double.MinValue;
this.Evaluate.SetTradeRules(chromosomes.SelectMany(c=>c.BuyCondition.TradeRules.Concat(c.SellCondition.TradeRules)));
Trades trades = null;
TradeCondition buyCond;
TradeCondition sellCond;
int totalTrades = 0;
int winners = 0;
int losers = 0;
int stopout = 0;
Chromosome chr = null;
for (int i = 0; i < chromosomes.Count; i++)
{
chr = chromosomes[i];
buyCond = chr.BuyCondition;
sellCond = chr.SellCondition;
trades = this.Evaluate.EvalTrades(tradeSystem, buyCond, sellCond, stopOutValue);
double endingCapital = Math.Round((tradeSystem.FinancialSettings.InitialCapital + trades.TradeTable.Select().Sum(r => (double)r["Profit"])), 2);
currentFitnessValue = endingCapital > 0 ? endingCapital : 0;
if (!Proceed)
{
return list;
}
if (bestFitnessValue < currentFitnessValue)
{
bestChromosome = chr;
bestFitnessValue = currentFitnessValue;
winners = this.Evaluate.Winners;
losers = this.Evaluate.Losers;
stopout = this.Evaluate.StopOuts;
totalTrades = trades.Count();
}
dynamic d = new System.Dynamic.ExpandoObject();
d.FitnessValue = currentFitnessValue;
d.Chromosome = chr;
list.Add(d);
}
TradeSystem ts = tradeSystem.CloneWithOutConditions();
ts.BuyCondition = bestChromosome.BuyCondition;
ts.SellCondition = bestChromosome.SellCondition;
GeneticResult result = new GeneticResult(ts, bestFitnessValue, winners, losers, totalTrades, stopout, iteration, generation);
if (this.BestResult == null || this.BestResult.FitnessValue < result.FitnessValue)
{
this.BestResult = result;
}
this.BestResult.Iteration = iteration;
this.BestResult.Generation = generation;
return list.OrderByDescending(d => d.FitnessValue).ToList();
}