public void Initialize()
{
//parameters.eselectionMethod= ESelectionMethod.
if (parameters == null)
{
parameters = new GPParameters();
}
parameters.einitializationMethod = mGPModelParameter.PopulatonInitialization;
parameters.eselectionMethod = mGPModelParameter.SelectionMethod;
parameters.efitnessFunction = mGPModelParameter.Fitness;
parameters.InitiFitness();
parameters.SelParam1 = mGPModelParameter.SelectionParam1;
parameters.SelParam2 = mGPModelParameter.SelectionParam2;
parameters.maxInitLevel = mGPModelParameter.MaxInitLevel;
parameters.maxCossoverLevel = mGPModelParameter.MaxCossoverLevel;
parameters.maxMutationLevel = mGPModelParameter.MaxMutationLevel;
parameters.elitism = mGPModelParameter.Elitism;
parameters.probCrossover = mGPModelParameter.ProbCrossover;
parameters.probMutation = mGPModelParameter.ProbMutation;
parameters.probPermutation = mGPModelParameter.ProbPermutation;
parameters.probReproduction = mGPModelParameter.ProbReproduction;
}
/// <summary>
/// Set GUI based on the GPParameters
/// </summary>
/// <param name="parameters"></param>
/// <returns></returns>
public bool SetParameters(GPParameters parameters)
{
txtPopSize.Text = parameters.popSize.ToString();
cmbSelectionMethods.SelectedIndex = (int)parameters.eselectionMethod;
cmbFitnessFuncs.SelectedIndex = getFitnessSelectedIndex(parameters.GPFitness);
txtElitism.Text = parameters.elitism.ToString();
cmbInitMethods.SelectedIndex = (int)parameters.einitializationMethod;
txtSelParam1.Text = parameters.SelParam1.ToString();
txtSelParam2.Text = parameters.SelParam1.ToString();
txtInitTreeDepth.Text = parameters.maxInitLevel.ToString();
txtOperationTreeDepth.Text = parameters.maxOperationLevel.ToString();
txtProbCrossover.Text = parameters.probCrossover.ToString();
txtProbMutation.Text = parameters.probMutation.ToString();
txtProbReproduction.Text = parameters.probReproduction.ToString();
//txtProbPermutation.Text = parameters.probPermutation.ToString();
//txtProbEncaptulation.Text = "ewe";
txtRandomConsTo.Text = parameters.rConstTo.ToString();
txtRandomConsFrom.Text = parameters.rConstFrom.ToString();
txtRandomConstNum.Text = parameters.rConstNum.ToString();
radioIsParallel.Checked = parameters.bParalelGP;
///
txtBroodSize.Text = parameters.broodSize.ToString();
isProtectedOperation.Checked = parameters.isProtectedOperationEnabled;
return(true);
}
/// <summary>
/// Before we start GP prepare all neccessery information
/// </summary>
/// <param name="termSet"></param>
/// <param name="funSet"></param>
/// <param name="gpParams"></param>
public void PrepareAlgorithm(GPTerminalSet termSet, GPFunctionSet funSet, GPParameters gpParams = null)
{
m_IterationCounter = 0;
if (Population == null)
{
Population = new CHPopulation();
}
Population.InitPopulation(termSet, funSet, gpParams);
Population.CalculatePopulation();
IsAlgorthmPrepared = true;
StopIteration = false;
//calculate model and prediction
GPChromosome ch = Population.bestChromosome as GPChromosome;
double[][] model = CalculateModel(ch);
double[][] prediction = CalculateModel(ch, false);
//Report the evolution has been started
if (ReportEvolution != null)
{
ReportEvolution(this,
new ProgressIndicatorEventArgs()
{
ReportType = ProgramState.Started,
AverageFitness = Population.fitnessAvg,
BestChromosome = Population.bestChromosome,
CurrentIteration = 0, LearnOutput = model, PredicOutput = prediction
});
}
}
/// <summary>
/// Initialisation of chromosomes in Genetic programming
/// </summary>
/// <param name="size">Size of the chromosomes, default value is 1000</param>
/// <param name="initMethod">Initializastion method, default HalfandHalf</param>
public void InitPopulation(
GPTerminalSet termSet,
GPFunctionSet funSet,
GPParameters gpParams = null
)
{
if (gpParams == null)
{
gpParameters = new GPParameters();
}
else
{
gpParameters = gpParams;
}
fitnessFunction = gpParameters.GPFitness;
if (funSet == null)
{
throw new Exception("FunctionSet is not defined, and cannot be null!");
}
{
functionSet = funSet;
Globals.functions = functionSet;
}
if (funSet == null)
{
throw new Exception("TerminalSet is not defined, and cannot be null!");
}
Globals.terminals = termSet;
GeneratePopulation(gpParameters.popSize);
}
public void SetGPParameter(GPParameters gpp)
{
Population.SetParameters(gpp);
}
/// <summary>
/// Return current value of GP params
/// </summary>
/// <returns></returns>
public GPParameters GetParameters()
{
GPParameters parameters = new GPParameters();
parameters.einitializationMethod = (GPInitializationMethod)cmbInitMethods.SelectedIndex;
parameters.eselectionMethod = (GPSelectionMethod)cmbSelectionMethods.SelectedIndex;
//
parameters.GPFitness = SelectFitnessFun(cmbFitnessFuncs.SelectedIndex);
// parameters.InitiFitness();
if (!int.TryParse(txtPopSize.Text, out parameters.popSize))
{
MessageBox.Show("Invalid value for Population size!");
return(null);
}
if (!int.TryParse(txtElitism.Text, out parameters.elitism))
{
MessageBox.Show("Invalid value for Elitism!");
return(null);
}
if (!float.TryParse(txtSelParam1.Text, out parameters.SelParam1))
{
MessageBox.Show("Invalid value for Parameter 1!");
return(null);
}
if (!float.TryParse(txtSelParam2.Text, out parameters.SelParam2))
{
MessageBox.Show("Invalid value for Parameter 2!");
return(null);
}
if (!int.TryParse(txtInitTreeDepth.Text, out parameters.maxInitLevel))
{
MessageBox.Show("Invalid value for Initial tree depth!");
return(null);
}
if (!int.TryParse(txtOperationTreeDepth.Text, out parameters.maxOperationLevel))
{
MessageBox.Show("Invalid value for Operation tree depth!");
return(null);
}
parameters.bParalelGP = radioIsParallel.Checked;
if (!float.TryParse(txtRandomConsFrom.Text, out parameters.rConstFrom))
{
MessageBox.Show("Invalid value for interval to!");
return(null);
}
if (!float.TryParse(txtRandomConsTo.Text, out parameters.rConstTo))
{
MessageBox.Show("Invalid value for interval from!");
return(null);
}
if (!int.TryParse(txtRandomConstNum.Text, out parameters.rConstNum))
{
MessageBox.Show("Invalid value for Number of Constants!");
return(null);
}
if (parameters.rConstNum < 0)
{
MessageBox.Show("Invalid value for Number of Constants!");
return(null);
}
if (!float.TryParse(txtProbCrossover.Text, out parameters.probCrossover))
{
MessageBox.Show("Invalid value for Crossover probability!");
return(null);
}
if (!float.TryParse(txtProbMutation.Text, out parameters.probMutation))
{
MessageBox.Show("Invalid value for Mutation probability!");
return(null);
}
if (!float.TryParse(txtProbReproduction.Text, out parameters.probReproduction))
{
MessageBox.Show("Invalid value for Reproduction probability!");
return(null);
}
if (!int.TryParse(txtBroodSize.Text, out parameters.broodSize))
{
MessageBox.Show("Invalid Brood Size value!");
return(null);
}
parameters.isProtectedOperationEnabled = isProtectedOperation.Checked;
return(parameters);
}
/// <summary>
///
/// </summary>
/// <param name="gpp"></param>
internal void SetParameters(GPParameters gpp)
{
Globals.gpparameters = gpp;
}
/// <summary>
/// Initialisation of chromosomes in Genetic programming
/// </summary>
/// <param name="size">Size of the chromosomes, default value is 1000</param>
/// <param name="initMethod">Initializastion method, default HalfandHalf</param>
public void InitPopulation(
GPTerminalSet termSet,
IFunctionSet funSet,
GPParameters gpParams = null
)
{
if (gpParams == null)
{
Globals.gpparameters = new GPParameters();
}
else
{
Globals.gpparameters = gpParams;
}
if (Globals.gpparameters.algorithmType == Algorithm.GA)
{
if (Globals.gpparameters.chromosomeKind == GAChromosome.Continue)
{
GANumChromosome.functionSet = funSet;
}
else if (Globals.gpparameters.chromosomeKind == GAChromosome.TSP)
{
GAVChromosome.functionSet = funSet;
}
else if (Globals.gpparameters.chromosomeKind == GAChromosome.ALOC)
{
GAVChromosome.functionSet = funSet;
}
else if (Globals.gpparameters.chromosomeKind == GAChromosome.TP)
{
GAMChromosome.terminalSet = termSet;
GAMChromosome.functionSet = funSet;
}
else
{
GABinChromosome.functionSet = funSet;
}
}
else
{
GPChromosome.MaxOperationLevel = Globals.gpparameters.maxOperationLevel;
}
//init default fitness type
if (Globals.gpparameters.GPFitness == null)
{
Globals.gpparameters.GPFitness = new RMSEFitness();
}
fitnessFunction = Globals.gpparameters.GPFitness;
if (funSet == null)
{
throw new Exception("FunctionSet is not defined, and cannot be null!");
}
else
{
functionSet = funSet;
Globals.functions = functionSet;
}
if (termSet == null)
{
throw new Exception("TerminalSet is not defined, and cannot be null!");
}
else
{
Globals.gpterminals = termSet;
}
var siz = Globals.gpparameters.popSize - chromosomes.Count;
if (siz > 0)
{
GeneratePopulation(siz);
}
}
