private void Initialize(IEnumerable<string> variableNames, int nConstants) { #region symbol declaration var add = new Addition(); var sub = new Subtraction(); var mul = new Multiplication(); var div = new Division(); var mean = new Average(); var log = new Logarithm(); var pow = new Power(); var square = new Square(); var root = new Root(); var sqrt = new SquareRoot(); var exp = new Exponential(); // we use our own random number generator here because we assume // that grammars are only initialized once when setting the grammar in the problem. // This means everytime the grammar parameter in the problem is changed // we initialize the constants to new values var rand = new MersenneTwister(); // warm up for (int i = 0; i < 1000; i++) rand.NextDouble(); var constants = new List<Constant>(nConstants); for (int i = 0; i < nConstants; i++) { var constant = new Constant(); do { var constVal = rand.NextDouble() * 20.0 - 10.0; constant.Name = string.Format("{0:0.000}", constVal); constant.MinValue = constVal; constant.MaxValue = constVal; constant.ManipulatorSigma = 0.0; constant.ManipulatorMu = 0.0; constant.MultiplicativeManipulatorSigma = 0.0; } while (constants.Any(c => c.Name == constant.Name)); // unlikely, but it could happen that the same constant value is sampled twice. so we resample if necessary. constants.Add(constant); } var variables = new List<HeuristicLab.Problems.DataAnalysis.Symbolic.Variable>(); foreach (var variableName in variableNames) { var variableSymbol = new HeuristicLab.Problems.DataAnalysis.Symbolic.Variable(); variableSymbol.Name = variableName; variableSymbol.WeightManipulatorMu = 0.0; variableSymbol.WeightManipulatorSigma = 0.0; variableSymbol.WeightMu = 1.0; variableSymbol.WeightSigma = 0.0; variableSymbol.MultiplicativeWeightManipulatorSigma = 0.0; variableSymbol.AllVariableNames = new[] { variableName }; variableSymbol.VariableNames = new[] { variableName }; variables.Add(variableSymbol); } #endregion AddSymbol(add); AddSymbol(sub); AddSymbol(mul); AddSymbol(div); AddSymbol(mean); AddSymbol(log); AddSymbol(pow); AddSymbol(square); AddSymbol(root); AddSymbol(sqrt); AddSymbol(exp); constants.ForEach(AddSymbol); variables.ForEach(AddSymbol); #region subtree count configuration SetSubtreeCount(add, 2, 2); SetSubtreeCount(sub, 2, 2); SetSubtreeCount(mul, 2, 2); SetSubtreeCount(div, 2, 2); SetSubtreeCount(mean, 2, 2); SetSubtreeCount(log, 1, 1); SetSubtreeCount(pow, 2, 2); SetSubtreeCount(square, 1, 1); SetSubtreeCount(root, 2, 2); SetSubtreeCount(sqrt, 1, 1); SetSubtreeCount(exp, 1, 1); constants.ForEach((c) => SetSubtreeCount(c, 0, 0)); variables.ForEach((v) => SetSubtreeCount(v, 0, 0)); #endregion var functions = new ISymbol[] { add, sub, mul, div, mean, log, pow, root, square, sqrt }; var terminalSymbols = variables.Concat<ISymbol>(constants); var allSymbols = functions.Concat(terminalSymbols); #region allowed child symbols configuration foreach (var s in allSymbols) { AddAllowedChildSymbol(StartSymbol, s); } foreach (var parentSymb in functions) foreach (var childSymb in allSymbols) { AddAllowedChildSymbol(parentSymb, childSymb); } #endregion }
public static Dataset CreateRandomDataset(MersenneTwister twister, int rows, int columns) { double[,] data = new double[rows, columns]; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { data[i, j] = twister.NextDouble() * 2.0 - 1.0; } } IEnumerable<string> variableNames = new string[] { "y" }.Concat(Enumerable.Range(0, columns - 1).Select(x => "x" + x.ToString())); Dataset ds = new Dataset(variableNames, data); return ds; }