public IList<GeneScore> Run(IList<BaseChromosomeType> chromosomeTypes, OptimiserParameters parameters)
{
var allScores = new List<GeneScore>();
var exiting = false;
var iterationCount = 0;
var totalIterations = parameters.MaximumGenerations * parameters.PopulationSize;
var geneValidator = GetGeneValidator(chromosomeTypes, parameters.ParameterConditions);
var evolver = new Evolver(chromosomeTypes, parameters.Seed,
new CompositeGeneValidator(geneValidator, new OnceOnlyGeneValidator()));
evolver.ReportNoProgress += ReportNoProgress;
evolver.ReportNoProgress += delegate(object sender, CancelEventArgs args) { exiting |= args.Cancel; };
_fitnessEvaluator.Initialise(parameters);
IList<Gene> population = evolver.GetInitialPopulation(parameters.PopulationSize);
for (var generation = 0; generation < parameters.MaximumGenerations; generation++)
{
var scoresThisGeneration = new List<GeneScore>();
foreach (var gene in population)
{
var score = _fitnessEvaluator.Evaluate(gene);
scoresThisGeneration.Add(score);
iterationCount++;
if (OnIterationComplete(score, iterationCount, totalIterations - iterationCount))
{
exiting = true;
break;
}
}
scoresThisGeneration.Sort();
if (exiting)
{
break;
}
population = evolver.GetNextGeneration(parameters.ReproductionRate, parameters.MutationRate,
scoresThisGeneration.ConvertAll(score => score.Gene));
allScores.AddRange(scoresThisGeneration);
OnGenerationComplete(generation, scoresThisGeneration);
}
allScores.Sort();
OnComplete();
return allScores;
}
public IList <GeneScore> Run(IList <BaseChromosomeType> chromosomeTypes, OptimiserParameters parameters)
{
var allScores = new List <GeneScore>();
var exiting = false;
var iterationCount = 0;
var totalIterations = parameters.MaximumGenerations * parameters.PopulationSize;
var geneValidator = GetGeneValidator(chromosomeTypes, parameters.ParameterConditions);
var evolver = new Evolver(chromosomeTypes, parameters.Seed,
new CompositeGeneValidator(geneValidator, new OnceOnlyGeneValidator()));
evolver.ReportNoProgress += ReportNoProgress;
evolver.ReportNoProgress += delegate(object sender, CancelEventArgs args) { exiting |= args.Cancel; };
_fitnessEvaluator.Initialise(parameters);
IList <Gene> population = evolver.GetInitialPopulation(parameters.PopulationSize);
for (var generation = 0; generation < parameters.MaximumGenerations; generation++)
{
var scoresThisGeneration = new List <GeneScore>();
foreach (var gene in population)
{
var score = _fitnessEvaluator.Evaluate(gene);
scoresThisGeneration.Add(score);
iterationCount++;
if (OnIterationComplete(score, iterationCount, totalIterations - iterationCount))
{
exiting = true;
break;
}
}
scoresThisGeneration.Sort();
if (exiting)
{
break;
}
population = evolver.GetNextGeneration(parameters.ReproductionRate, parameters.MutationRate,
scoresThisGeneration.ConvertAll(score => score.Gene));
allScores.AddRange(scoresThisGeneration);
OnGenerationComplete(generation, scoresThisGeneration);
}
allScores.Sort();
OnComplete();
return(allScores);
}
public static void Initialise(OptimiserParameters optimiserParameters, StrategyBase strategy)
{
_minimumTrades = optimiserParameters.MinimumTrades;
_maximumTrades = optimiserParameters.MaximumTrades;
_optimisationType =
(OptimizationType) Activator.CreateInstance(Type.GetType(optimiserParameters.FitnessFunctionType));
_optimisationType.Strategy = strategy;
}
public void Initialise(OptimiserParameters parameters, IList<BaseChromosomeType> chromosomeTypes)
{
_validatorFactory = new GeneValidatorFactory(chromosomeTypes);
generationsSpin.Value = parameters.MaximumGenerations;
populationSizeSpin.Value = parameters.PopulationSize;
reproductionPercentSpin.Value = (decimal) (parameters.ReproductionRate * 100);
mutationRateSpin.Value = (decimal) (parameters.MutationRate * 100);
screenThresholdSpin.Value = (decimal) parameters.ScreeningThreshold;
saveLogCheckbox.Checked = parameters.ExportGenes;
var wrappers = GetOptimisationTypeWrappers();
fitnessFunctionComboBox.DisplayMember = "Name";
fitnessFunctionComboBox.ValueMember = "Type";
fitnessFunctionComboBox.DataSource = wrappers;
try
{
foreach (var wrapper in wrappers)
{
if (wrapper.Type.AssemblyQualifiedName == parameters.FitnessFunctionType)
{
fitnessFunctionComboBox.SelectedItem = wrapper;
break;
}
}
}
catch
{
}
minimumTradesSpin.Value = parameters.MinimumTrades;
strategyParameterConditionsGrid.Rows.Clear();
foreach (var condition in parameters.ParameterConditions)
{
if (IsConditionValid(condition))
{
var row = strategyParameterConditionsGrid.Rows[strategyParameterConditionsGrid.Rows.Add()];
row.SetValues(condition);
}
}
}
public void Initialise(OptimiserParameters parameters)
{
FitnessFunctionWrapper.Initialise(parameters, _strategy);
}
static MoGoNT()
{
__lastParameters = GetStartingParameters();
}
private void SaveParameters(OptimiserParameters parameters)
{
try
{
var parametersSerialiser = new XmlSerializer(typeof (OptimiserParameters));
using (var xmlTextWriter = new XmlTextWriter(ParametersFilename, Encoding.ASCII))
{
xmlTextWriter.Formatting = Formatting.Indented;
parametersSerialiser.Serialize(xmlTextWriter, parameters);
}
}
catch
{
}
}
private OptimiserParameters GetParameters(IList<BaseChromosomeType> chromosomeTypes)
{
_parametersForm = new ParametersForm();
_parametersForm.Initialise(__lastParameters, chromosomeTypes);
OptimiserParameters parameters = null;
_parametersForm.ParametersSet +=
delegate(object sender, ParameterEventArgs args) { parameters = args.Parameters; };
_parametersForm.ShowDialog();
//while (parameters == null)
//{
// Application.DoEvents();
//}
__lastParameters = parameters;
SaveParameters(parameters);
return parameters;
}
private static OptimiserParameters GetStartingParameters()
{
OptimiserParameters parameters = null;
try
{
if (File.Exists(ParametersFilename))
{
var parametersSerialiser = new XmlSerializer(typeof (OptimiserParameters));
using (var stream = File.OpenRead(ParametersFilename))
{
parameters = (OptimiserParameters) parametersSerialiser.Deserialize(stream);
}
}
}
catch
{
}
if (parameters == null)
{
parameters = new OptimiserParameters(5, 256, 0.1, 0.05, 0, false, null, string.Empty, 50, 1000,
new List<string>());
}
return parameters;
}
public ParameterEventArgs(OptimiserParameters parameters)
{
_parameters = parameters;
}