private ISymbolicExpressionTreeNode GenTreeShiftStdDist(string variable, double m_org, double s_org, double m_tar, double s_tar)
{
// x - m_org
var substractionNode = new Subtraction().CreateTreeNode();
var xNode = CreateVariableTreeNode(variable, "x");
var m_orgNode = CreateConstantTreeNode("m_org", m_org);
substractionNode.AddSubtree(xNode);
substractionNode.AddSubtree(m_orgNode);
// (x - m_org) / s_org
var divisionNode = new Division().CreateTreeNode();
var s_orgNode = CreateConstantTreeNode("s_org", s_org);
divisionNode.AddSubtree(substractionNode);
divisionNode.AddSubtree(s_orgNode);
// ((x - m_org) / s_org ) * s_tar
var multiplicationNode = new Multiplication().CreateTreeNode();
var s_tarNode = CreateConstantTreeNode("s_tar", s_tar);
multiplicationNode.AddSubtree(divisionNode);
multiplicationNode.AddSubtree(s_tarNode);
// ((x - m_org) / s_org ) * s_tar + m_tar
var additionNode = new Addition().CreateTreeNode();
var m_tarNode = CreateConstantTreeNode("m_tar", m_tar);
additionNode.AddSubtree(multiplicationNode);
additionNode.AddSubtree(m_tarNode);
return(additionNode);
}
public static ISymbolicExpressionTree CreateTree(string[] variableNames, int[] lags, double[] coefficients,
double @const = 0)
{
if (variableNames.Length == 0 ||
variableNames.Length != coefficients.Length ||
variableNames.Length != lags.Length)
{
throw new ArgumentException("The length of the variable names, lags, and coefficients vectors must match");
}
ISymbolicExpressionTree tree = new SymbolicExpressionTree(new ProgramRootSymbol().CreateTreeNode());
ISymbolicExpressionTreeNode startNode = new StartSymbol().CreateTreeNode();
tree.Root.AddSubtree(startNode);
ISymbolicExpressionTreeNode addition = new Addition().CreateTreeNode();
startNode.AddSubtree(addition);
for (int i = 0; i < variableNames.Length; i++)
{
if (lags[i] == 0)
{
VariableTreeNode vNode = (VariableTreeNode) new Variable().CreateTreeNode();
vNode.VariableName = variableNames[i];
vNode.Weight = coefficients[i];
addition.AddSubtree(vNode);
}
else
{
LaggedVariableTreeNode vNode = (LaggedVariableTreeNode) new LaggedVariable().CreateTreeNode();
vNode.VariableName = variableNames[i];
vNode.Weight = coefficients[i];
vNode.Lag = lags[i];
addition.AddSubtree(vNode);
}
}
if ([email protected](0.0))
{
ConstantTreeNode cNode = (ConstantTreeNode) new Constant().CreateTreeNode();
cNode.Value = @const;
addition.AddSubtree(cNode);
}
return(tree);
}
// helper
private ISymbolicExpressionTreeNode GenerateModelForLinearTransformation()
{
var linearTransformation = (LinearTransformation)transformation;
var kValue = linearTransformation.Multiplier;
var dValue = linearTransformation.Addend;
// k * x
var multiplicationNode = new Multiplication().CreateTreeNode();
var kNode = CreateConstantTreeNode("k", kValue);
var xNode = CreateVariableTreeNode(column, "x");
multiplicationNode.AddSubtree(kNode);
multiplicationNode.AddSubtree(xNode);
// ( k * x ) + d
var additionNode = new Addition().CreateTreeNode();
var dNode = CreateConstantTreeNode("d", dValue);
additionNode.AddSubtree(multiplicationNode);
additionNode.AddSubtree(dNode);
return(additionNode);
}
public static ISymbolicExpressionTree CreateTree(IEnumerable <KeyValuePair <string, IEnumerable <string> > > factors,
double[] factorCoefficients,
double @const = 0)
{
ISymbolicExpressionTree tree = new SymbolicExpressionTree(new ProgramRootSymbol().CreateTreeNode());
ISymbolicExpressionTreeNode startNode = new StartSymbol().CreateTreeNode();
tree.Root.AddSubtree(startNode);
ISymbolicExpressionTreeNode addition = new Addition().CreateTreeNode();
startNode.AddSubtree(addition);
int i = 0;
foreach (var factor in factors)
{
var varName = factor.Key;
foreach (var factorValue in factor.Value)
{
var node = (BinaryFactorVariableTreeNode) new BinaryFactorVariable().CreateTreeNode();
node.VariableValue = factorValue;
node.VariableName = varName;
node.Weight = factorCoefficients[i];
addition.AddSubtree(node);
i++;
}
}
if ([email protected](0.0))
{
ConstantTreeNode cNode = (ConstantTreeNode) new Constant().CreateTreeNode();
cNode.Value = @const;
addition.AddSubtree(cNode);
}
return(tree);
}
private static ISymbolicRegressionSolution CreateSymbolicSolution(List<IRegressionModel> models, double nu, IRegressionProblemData problemData) {
var symbModels = models.OfType<ISymbolicRegressionModel>();
var lowerLimit = symbModels.Min(m => m.LowerEstimationLimit);
var upperLimit = symbModels.Max(m => m.UpperEstimationLimit);
var interpreter = new SymbolicDataAnalysisExpressionTreeLinearInterpreter();
var progRootNode = new ProgramRootSymbol().CreateTreeNode();
var startNode = new StartSymbol().CreateTreeNode();
var addNode = new Addition().CreateTreeNode();
var mulNode = new Multiplication().CreateTreeNode();
var scaleNode = (ConstantTreeNode)new Constant().CreateTreeNode(); // all models are scaled using the same nu
scaleNode.Value = nu;
foreach (var m in symbModels) {
var relevantPart = m.SymbolicExpressionTree.Root.GetSubtree(0).GetSubtree(0); // skip root and start
addNode.AddSubtree((ISymbolicExpressionTreeNode)relevantPart.Clone());
}
mulNode.AddSubtree(addNode);
mulNode.AddSubtree(scaleNode);
startNode.AddSubtree(mulNode);
progRootNode.AddSubtree(startNode);
var t = new SymbolicExpressionTree(progRootNode);
var combinedModel = new SymbolicRegressionModel(problemData.TargetVariable, t, interpreter, lowerLimit, upperLimit);
var sol = new SymbolicRegressionSolution(combinedModel, problemData);
return sol;
}
