public void PerformCrossover(ref IGenoType genoTypeLeft, ref IGenoType genoTypeRight)
{
if ((new PhenoTypeTree(genoTypeLeft.GenoTypeNodes)).ToString().Equals((new PhenoTypeTree(genoTypeRight.GenoTypeNodes)).ToString()))
{
return;
}
// var left1 = new PhenoTypeTree(genoTypeLeft.GenoTypeNodes).ToString();
// var right1 = new PhenoTypeTree(genoTypeRight.GenoTypeNodes).ToString();
if (!(UniformRandomGenerator.GetContinousRandomNumber(0, 1.0) <= EaGeneExpressionParameters.CrossoverProbability))
{
return;
}
if (UniformRandomGenerator.GetContinousRandomNumber(0, 1.0) < 0.5)
{
var numberOfNodes = PhenoTypeTree.GetNumberOfNodes(genoTypeLeft.GenoTypeNodes);
var crossOverPosition1 = UniformRandomGenerator.GetIntegerRandomNumber(0, numberOfNodes - 1);
if (UniformRandomGenerator.GetContinousRandomNumber(0, 1.0) < 0.1)
{
for (var index = crossOverPosition1; index < genoTypeLeft.GenoTypeNodes.Count; index++)
{
Swap(genoTypeLeft.GenoTypeNodes, genoTypeRight.GenoTypeNodes, index);
}
}
else
{
for (var index = 0; index <= crossOverPosition1; index++)
{
Swap(genoTypeLeft.GenoTypeNodes, genoTypeRight.GenoTypeNodes, index);
}
}
}
else
{
var crossOverPosition1 = UniformRandomGenerator.GetIntegerRandomNumber(1, genoTypeLeft.GenoTypeNodes.Count - 2);
var crossOverPosition2 = UniformRandomGenerator.GetIntegerRandomNumber(crossOverPosition1, genoTypeLeft.GenoTypeNodes.Count - 2);
for (var index = crossOverPosition1; index < crossOverPosition2; index++)
{
Swap(genoTypeLeft.GenoTypeNodes, genoTypeRight.GenoTypeNodes, index);
}
}
// var left2 = new PhenoTypeTree(genoTypeLeft.GenoTypeNodes).ToString();
// var right2 = new PhenoTypeTree(genoTypeRight.GenoTypeNodes).ToString();
}
public void PerformMutation(ref IGenoType genoType)
{
if (!(UniformRandomGenerator.GetContinousRandomNumber(0, 1.0) <= EaGeneExpressionParameters.MutationProbability))
{
return;
}
var randomNumber = UniformRandomGenerator.GetContinousRandomNumber(0, 1.0);
if (randomNumber <= 0.3)
{
genoType = GenoTypeFactory.GetGenoType();
}
else
{
//var index = UniformRandomGenerator.GetIntegerRandomNumber(0, genoType.GenoTypeNodes.Count - 1);
var numberOfNodes = PhenoTypeTree.GetNumberOfNodes(genoType.GenoTypeNodes);
var index = UniformRandomGenerator.GetIntegerRandomNumber(0, numberOfNodes - 1);
if (randomNumber <= 0.6)
{
var node = genoType.GenoTypeNodes[index];
genoType.GenoTypeNodes.RemoveAt(index);
index = UniformRandomGenerator.GetIntegerRandomNumber(0, genoType.GenoTypeNodes.Count - 1);
genoType.GenoTypeNodes.Insert(index, node);
}
else
{
if (genoType.GenoTypeNodes[index].GetType() == typeof(ParameterTerminal))
{
((ParameterTerminal)genoType.GenoTypeNodes[index]).Value =
((ParameterTerminal)genoType.GenoTypeNodes[index]).Value +
UniformRandomGenerator.GetContinousRandomNumber(-3.0, 3.0);
}
else
{
if (index < EaGeneExpressionParameters.MaximumNumberOfHeadNodes)
{
genoType.GenoTypeNodes[index] = GenoTypeFactory.GetFunctionOrTerminalNode();
}
else
{
genoType.GenoTypeNodes[index] = GenoTypeFactory.GetTerminalNode();
}
}
}
}
}
public static IObjectiveValues GetObjectiveValues(Target <double> target, IDataSet dataSet, Individual individual)
{
var phenoTypeTree = new PhenoTypeTree(individual.GenoType.GenoTypeNodes);
var stringExpresssion = phenoTypeTree.ToString();
// TODO make mapped columns more sophisticated
var mappedColumnsUsedInExpression = new Dictionary <string, int>();
foreach (var mappedColumn in dataSet.MappedColumns)
{
if (stringExpresssion.Contains(mappedColumn.Key))
{
mappedColumnsUsedInExpression.Add(mappedColumn.Key.Replace("[", "").Replace("]", "").Trim(), mappedColumn.Value);
}
}
var expression = new Expression(stringExpresssion);
var numberOfRows = (double)dataSet.MappedData.GetLength(0);
double mae = 0;
//var rmse = 0m;
var maxError = 0m;
for (var row = 0; row < numberOfRows; row++)
{
foreach (var usedMappedColumn in mappedColumnsUsedInExpression)
{
expression.Parameters[usedMappedColumn.Key] = dataSet.MappedData[row, usedMappedColumn.Value];
}
if (!expression.HasErrors())
{
var prediction = (double)expression.Evaluate();
if (double.IsNaN(prediction) || double.IsInfinity(prediction))
{
mae = double.MaxValue;
//rmse = decimal.MaxValue;
//maxError = decimal.MaxValue;
break;
}
var error = prediction - target.Values[row];
var absError = Math.Abs(error);
//if (absError > (double) maxError)
//{
// if (absError <= (double) decimal.MaxValue)
// {
// maxError = (decimal)absError;
// }
// else
// {
// maxError = decimal.MaxValue;
// }
//}
mae = mae + Math.Abs(error);
}
else
{
mae = double.MaxValue;
//rmse = decimal.MaxValue;
//maxError = decimal.MaxValue;
break;
}
}
if (mae != double.MaxValue)
{
mae = Math.Log(mae + 1.0);
//mae = mae / numberOfRows;
}
var fix = 13;
if (mae >= (double)decimal.MaxValue)
{
mae = fix;
}
//if (rmse != decimal.MaxValue)
//{
//rmse = Sqrt( rmse / numberOfRows);
//}
var numberOfNodes = PhenoTypeTree.GetNumberOfNodes(individual.GenoType.GenoTypeNodes);
//var numberOfCharacters = stringExpresssion.Length;
//var distinctNumberOfFeatures = mappedColumnsUsedInExpression.Count;
//Console.WriteLine(mse + " " + numberOfOpenBrackets);
// string[] names = { "sMape", "OpenBrackets", "Mse" };
// double[] values = { sMape, numberOfOpenBrackets, mse };
string[] names = { "mae", "numberOfNodes" };
decimal[] values = { (decimal)mae, numberOfNodes };
var objectiveValues =
new ObjectiveValues(values, names, individual.Guid)
{
ExpressionForDebugging = stringExpresssion
};
if (mae == fix)
{
objectiveValues.Invalid = true;
}
return(objectiveValues);
}