private double CalculateReplacementValue(ISymbolicExpressionTreeNode node, ISymbolicExpressionTree sourceTree)
{
// remove old ADFs
while (tempTree.Root.SubtreeCount > 1)
{
tempTree.Root.RemoveSubtree(1);
}
// clone ADFs of source tree
for (int i = 1; i < sourceTree.Root.SubtreeCount; i++)
{
tempTree.Root.AddSubtree((ISymbolicExpressionTreeNode)sourceTree.Root.GetSubtree(i).Clone());
}
var start = tempTree.Root.GetSubtree(0);
while (start.SubtreeCount > 0)
{
start.RemoveSubtree(0);
}
start.AddSubtree((ISymbolicExpressionTreeNode)node.Clone());
var interpreter = Content.Model.Interpreter;
var rows = Content.ProblemData.TrainingIndices;
var allPrognosedValues = interpreter.GetSymbolicExpressionTreeValues(tempTree, Content.ProblemData.Dataset, rows);
return(allPrognosedValues.Median());
}
protected static double CalculateReplacementValue(ISymbolicExpressionTreeNode node, ISymbolicExpressionTree sourceTree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
IDataset dataset, IEnumerable <int> rows)
{
//optimization: constant nodes return always the same value
ConstantTreeNode constantNode = node as ConstantTreeNode;
if (constantNode != null)
{
return(constantNode.Value);
}
var rootSymbol = new ProgramRootSymbol().CreateTreeNode();
var startSymbol = new StartSymbol().CreateTreeNode();
rootSymbol.AddSubtree(startSymbol);
startSymbol.AddSubtree((ISymbolicExpressionTreeNode)node.Clone());
var tempTree = new SymbolicExpressionTree(rootSymbol);
// clone ADFs of source tree
for (int i = 1; i < sourceTree.Root.SubtreeCount; i++)
{
tempTree.Root.AddSubtree((ISymbolicExpressionTreeNode)sourceTree.Root.GetSubtree(i).Clone());
}
return(interpreter.GetSymbolicExpressionTreeValues(tempTree, dataset, rows).Median());
}
protected IEnumerable <double> CalculateReplacementValues(ISymbolicExpressionTreeNode node, ISymbolicExpressionTree sourceTree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
IDataset dataset, IEnumerable <int> rows)
{
//optimization: constant nodes return always the same value
ConstantTreeNode constantNode = node as ConstantTreeNode;
BinaryFactorVariableTreeNode binaryFactorNode = node as BinaryFactorVariableTreeNode;
FactorVariableTreeNode factorNode = node as FactorVariableTreeNode;
if (constantNode != null)
{
yield return(constantNode.Value);
}
else if (binaryFactorNode != null)
{
// valid replacements are either all off or all on
yield return(0);
yield return(1);
}
else if (factorNode != null)
{
foreach (var w in factorNode.Weights)
{
yield return(w);
}
yield return(0.0);
}
else
{
var rootSymbol = new ProgramRootSymbol().CreateTreeNode();
var startSymbol = new StartSymbol().CreateTreeNode();
rootSymbol.AddSubtree(startSymbol);
startSymbol.AddSubtree((ISymbolicExpressionTreeNode)node.Clone());
var tempTree = new SymbolicExpressionTree(rootSymbol);
// clone ADFs of source tree
for (int i = 1; i < sourceTree.Root.SubtreeCount; i++)
{
tempTree.Root.AddSubtree((ISymbolicExpressionTreeNode)sourceTree.Root.GetSubtree(i).Clone());
}
yield return(interpreter.GetSymbolicExpressionTreeValues(tempTree, dataset, rows).Median());
yield return(interpreter.GetSymbolicExpressionTreeValues(tempTree, dataset, rows).Average()); // TODO perf
}
}
protected static double CalculateReplacementValue(ISymbolicExpressionTreeNode node, ISymbolicExpressionTree sourceTree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
IDataset dataset, IEnumerable<int> rows) {
//optimization: constant nodes return always the same value
ConstantTreeNode constantNode = node as ConstantTreeNode;
if (constantNode != null) return constantNode.Value;
var rootSymbol = new ProgramRootSymbol().CreateTreeNode();
var startSymbol = new StartSymbol().CreateTreeNode();
rootSymbol.AddSubtree(startSymbol);
startSymbol.AddSubtree((ISymbolicExpressionTreeNode)node.Clone());
var tempTree = new SymbolicExpressionTree(rootSymbol);
// clone ADFs of source tree
for (int i = 1; i < sourceTree.Root.SubtreeCount; i++) {
tempTree.Root.AddSubtree((ISymbolicExpressionTreeNode)sourceTree.Root.GetSubtree(i).Clone());
}
return interpreter.GetSymbolicExpressionTreeValues(tempTree, dataset, rows).Median();
}
private void pasteToolStripMenuItem_Clicked(object sender, EventArgs e)
{
if (!(lastOp == EditOp.CopySubtree || lastOp == EditOp.CutSubtree))
{
return;
}
// check if the copied/cut node (stored in the tempNode) can be inserted as a child of the current selected node
var node = currSelected.Content;
if (node is ConstantTreeNode || node is VariableTreeNode)
{
return;
}
// check if the currently selected node can accept the copied node as a child
// no need to check the grammar, an arity check will do just fine here
if (node.Symbol.MaximumArity <= node.SubtreeCount)
{
return;
}
switch (lastOp)
{
case EditOp.CutSubtree: {
if (tempNode.IterateNodesBreadth().Contains(node))
{
throw new ArgumentException(); // cannot cut/paste a node into itself
}
ModifyTree(Tree, tempNode.Parent, tempNode, null); //remove node from its original parent
ModifyTree(Tree, node, null, tempNode); //insert it as a child to the new parent
break;
}
case EditOp.CopySubtree: {
var clone = (SymbolicExpressionTreeNode)tempNode.Clone();
ModifyTree(Tree, node, null, clone);
break;
}
}
currSelected = null; // because the tree will have changed
tempNode = null; // clear the clipboard after one paste
}
public static ISymbolicExpressionTreeNode Derive(ISymbolicExpressionTreeNode branch, string variableName)
{
if (branch.Symbol is Constant)
{
return(CreateConstant(0.0));
}
if (branch.Symbol is Variable)
{
var varNode = branch as VariableTreeNode;
if (varNode.VariableName == variableName)
{
return(CreateConstant(varNode.Weight));
}
else
{
return(CreateConstant(0.0));
}
}
if (branch.Symbol is Addition)
{
var sum = addSy.CreateTreeNode();
foreach (var subTree in branch.Subtrees)
{
sum.AddSubtree(Derive(subTree, variableName));
}
return(sum);
}
if (branch.Symbol is Subtraction)
{
var sum = subSy.CreateTreeNode();
foreach (var subTree in branch.Subtrees)
{
sum.AddSubtree(Derive(subTree, variableName));
}
return(sum);
}
if (branch.Symbol is Multiplication)
{
// (f * g)' = f'*g + f*g'
// for multiple factors: (f * g * h)' = ((f*g) * h)' = (f*g)' * h + (f*g) * h'
if (branch.SubtreeCount >= 2)
{
var f = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
var fprime = Derive(f, variableName);
for (int i = 1; i < branch.SubtreeCount; i++)
{
var g = (ISymbolicExpressionTreeNode)branch.GetSubtree(i).Clone();
var fg = Product((ISymbolicExpressionTreeNode)f.Clone(), (ISymbolicExpressionTreeNode)g.Clone());
var gPrime = Derive(g, variableName);
var fgPrime = Sum(Product(fprime, g), Product(gPrime, f));
// prepare for next iteration
f = fg;
fprime = fgPrime;
}
return(fprime);
}
else
{
// multiplication with only one argument has no effect -> derive the argument
return(Derive(branch.GetSubtree(0), variableName));
}
}
if (branch.Symbol is Division)
{
// (f/g)' = (f'g - g'f) / g²
if (branch.SubtreeCount == 1)
{
var g = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
var gPrime = Product(CreateConstant(-1.0), Derive(g, variableName));
var sqrNode = new Square().CreateTreeNode();
sqrNode.AddSubtree(g);
return(Div(gPrime, sqrNode));
}
else
{
// for two subtrees:
// (f/g)' = (f'g - fg')/g²
// if there are more than 2 subtrees
// div(x,y,z) is interpretered as (x/y)/z
// which is the same as x / (y*z)
// --> make a product of all but the first subtree and differentiate as for the 2-argument case above
var f = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
var g = Product(branch.Subtrees.Skip(1).Select(n => (ISymbolicExpressionTreeNode)n.Clone()));
var fprime = Derive(f, variableName);
var gprime = Derive(g, variableName);
var gSqr = Square(g);
return(Div(Subtract(Product(fprime, g), Product(f, gprime)), gSqr));
}
}
if (branch.Symbol is Logarithm)
{
var f = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
return(Product(Div(CreateConstant(1.0), f), Derive(f, variableName)));
}
if (branch.Symbol is Exponential)
{
var f = (ISymbolicExpressionTreeNode)branch.Clone();
return(Product(f, Derive(branch.GetSubtree(0), variableName)));
}
if (branch.Symbol is Square)
{
var f = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
return(Product(Product(CreateConstant(2.0), f), Derive(f, variableName)));
}
if (branch.Symbol is SquareRoot)
{
var f = (ISymbolicExpressionTreeNode)branch.Clone();
var u = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
return(Product(Div(CreateConstant(1.0), Product(CreateConstant(2.0), f)), Derive(u, variableName)));
}
if (branch.Symbol is CubeRoot)
{
var f = (ISymbolicExpressionTreeNode)branch.Clone();
var u = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
return(Product(Div(CreateConstant(1.0), Product(CreateConstant(3.0), Square(f))), Derive(u, variableName))); // 1/3 1/cbrt(f(x))^2 d/dx f(x)
}
if (branch.Symbol is Cube)
{
var f = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
return(Product(Product(CreateConstant(3.0), Square(f)), Derive(f, variableName)));
}
if (branch.Symbol is Absolute)
{
var f = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
var absf = Abs((ISymbolicExpressionTreeNode)f.Clone());
return(Product(Div(f, absf), Derive(f, variableName)));
}
if (branch.Symbol is AnalyticQuotient)
{
// aq(a(x), b(x)) = a(x) / sqrt(b(x)²+1)
var a = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
var b = (ISymbolicExpressionTreeNode)branch.GetSubtree(1).Clone();
var definition = Div(a, SquareRoot(Sum(Square(b), CreateConstant(1.0))));
return(Derive(definition, variableName));
}
if (branch.Symbol is Sine)
{
var u = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
var cos = (new Cosine()).CreateTreeNode();
cos.AddSubtree(u);
return(Product(cos, Derive(u, variableName)));
}
if (branch.Symbol is Cosine)
{
var u = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
var sin = (new Sine()).CreateTreeNode();
sin.AddSubtree(u);
return(Product(CreateConstant(-1.0), Product(sin, Derive(u, variableName))));
}
if (branch.Symbol is Tangent)
{
// tan(x)' = 1 / cos²(x)
var fxp = Derive(branch.GetSubtree(0), variableName);
var u = (ISymbolicExpressionTreeNode)branch.GetSubtree(0).Clone();
return(Div(fxp, Square(Cosine(u))));
}
if (branch.Symbol is HyperbolicTangent)
{
// tanh(f(x))' = f(x)'sech²(f(x)) = f(x)'(1 - tanh²(f(x)))
var fxp = Derive(branch.GetSubtree(0), variableName);
var tanh = (ISymbolicExpressionTreeNode)branch.Clone();
return(Product(fxp, Subtract(CreateConstant(1.0), Square(tanh))));
}
throw new NotSupportedException(string.Format("Symbol {0} is not supported.", branch.Symbol));
}
private ISymbolicExpressionTreeNode MakeIntegral(ISymbolicExpressionTreeNode subtree, int lag) {
if (lag == 0) return subtree;
else if (lag == -1 || lag == 1) {
return MakeSum(subtree, AddLagToDynamicNodes((ISymbolicExpressionTreeNode)subtree.Clone(), lag));
} else {
var node = (LaggedTreeNode)integralSymbol.CreateTreeNode();
node.Lag = lag;
node.AddSubtree(subtree);
return node;
}
}
private ISymbolicExpressionTreeNode SimplifyAny(ISymbolicExpressionTreeNode original) {
// can't simplify this function but simplify all subtrees
List<ISymbolicExpressionTreeNode> subtrees = new List<ISymbolicExpressionTreeNode>(original.Subtrees);
while (original.Subtrees.Count() > 0) original.RemoveSubtree(0);
var clone = (SymbolicExpressionTreeNode)original.Clone();
List<ISymbolicExpressionTreeNode> simplifiedSubtrees = new List<ISymbolicExpressionTreeNode>();
foreach (var subtree in subtrees) {
simplifiedSubtrees.Add(GetSimplifiedTree(subtree));
original.AddSubtree(subtree);
}
foreach (var simplifiedSubtree in simplifiedSubtrees) {
clone.AddSubtree(simplifiedSubtree);
}
if (simplifiedSubtrees.TrueForAll(t => IsConstant(t))) {
SimplifyConstantExpression(clone);
}
return clone;
}
/// <summary>
/// Creates a new simplified tree
/// </summary>
/// <param name="original"></param>
/// <returns></returns>
public ISymbolicExpressionTreeNode GetSimplifiedTree(ISymbolicExpressionTreeNode original) {
if (IsConstant(original) || IsVariable(original)) {
return (ISymbolicExpressionTreeNode)original.Clone();
} else if (IsAddition(original)) {
return SimplifyAddition(original);
} else if (IsSubtraction(original)) {
return SimplifySubtraction(original);
} else if (IsMultiplication(original)) {
return SimplifyMultiplication(original);
} else if (IsDivision(original)) {
return SimplifyDivision(original);
} else if (IsAverage(original)) {
return SimplifyAverage(original);
} else if (IsLog(original)) {
return SimplifyLog(original);
} else if (IsExp(original)) {
return SimplifyExp(original);
} else if (IsSquare(original)) {
return SimplifySquare(original);
} else if (IsSquareRoot(original)) {
return SimplifySquareRoot(original);
} else if (IsPower(original)) {
return SimplifyPower(original);
} else if (IsRoot(original)) {
return SimplifyRoot(original);
} else if (IsSine(original)) {
return SimplifySine(original);
} else if (IsCosine(original)) {
return SimplifyCosine(original);
} else if (IsTangent(original)) {
return SimplifyTangent(original);
} else if (IsIfThenElse(original)) {
return SimplifyIfThenElse(original);
} else if (IsGreaterThan(original)) {
return SimplifyGreaterThan(original);
} else if (IsLessThan(original)) {
return SimplifyLessThan(original);
} else if (IsAnd(original)) {
return SimplifyAnd(original);
} else if (IsOr(original)) {
return SimplifyOr(original);
} else if (IsNot(original)) {
return SimplifyNot(original);
} else if (IsTimeLag(original)) {
return SimplifyTimeLag(original);
} else if (IsIntegral(original)) {
return SimplifyIntegral(original);
} else {
return SimplifyAny(original);
}
}
private double CalculateReplacementValue(ISymbolicExpressionTreeNode node, ISymbolicExpressionTree sourceTree) {
// remove old ADFs
while (tempTree.Root.SubtreeCount > 1) tempTree.Root.RemoveSubtree(1);
// clone ADFs of source tree
for (int i = 1; i < sourceTree.Root.SubtreeCount; i++) {
tempTree.Root.AddSubtree((ISymbolicExpressionTreeNode)sourceTree.Root.GetSubtree(i).Clone());
}
var start = tempTree.Root.GetSubtree(0);
while (start.SubtreeCount > 0) start.RemoveSubtree(0);
start.AddSubtree((ISymbolicExpressionTreeNode)node.Clone());
var interpreter = Content.Model.Interpreter;
var rows = Content.ProblemData.TrainingIndices;
var allPrognosedValues = interpreter.GetSymbolicExpressionTreeValues(tempTree, Content.ProblemData.Dataset, rows);
return allPrognosedValues.Median();
}