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Timestamp:
02/28/20 14:55:58 (5 years ago)
Author:
pfleck
Message:

#3040

  • Added full functional grammar for vectors.
  • Added sum and mean aggregation for vectors.
File:
1 copied

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  • branches/3040_VectorBasedGP/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Grammars/FullFunctionalVectorExpressionGrammar.cs

    r17456 r17460  
    2626using HeuristicLab.Core;
    2727using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
     28using DoubleVector = MathNet.Numerics.LinearAlgebra.Vector<double>;
    2829
    2930namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
    30   [StorableType("44B0829C-1CB5-4BE9-9514-BBA54FAB2912")]
    31   [Item("FullFunctionalExpressionGrammar", "Represents a grammar for functional expressions using all available functions.")]
    32   public class FullFunctionalExpressionGrammar : DataAnalysisGrammar, ISymbolicDataAnalysisGrammar {
     31  [StorableType("C913F5C6-AF16-4F2C-BA93-2D5AE1F8E68A")]
     32  [Item("FullFunctionalVectorExpressionGrammar", "Represents a grammar for functional expressions using all available functions.")]
     33  public class FullFunctionalVectorExpressionGrammar : DataAnalysisGrammar, ISymbolicDataAnalysisGrammar {
    3334    [StorableConstructor]
    34     protected FullFunctionalExpressionGrammar(StorableConstructorFlag _) : base(_) { }
    35     protected FullFunctionalExpressionGrammar(FullFunctionalExpressionGrammar original, Cloner cloner) : base(original, cloner) { }
    36     public FullFunctionalExpressionGrammar()
    37       : base(ItemAttribute.GetName(typeof(FullFunctionalExpressionGrammar)), ItemAttribute.GetDescription(typeof(FullFunctionalExpressionGrammar))) {
     35    protected FullFunctionalVectorExpressionGrammar(StorableConstructorFlag _) : base(_) { }
     36    protected FullFunctionalVectorExpressionGrammar(FullFunctionalVectorExpressionGrammar original, Cloner cloner) : base(original, cloner) { }
     37    public FullFunctionalVectorExpressionGrammar()
     38      : base(ItemAttribute.GetName(typeof(FullFunctionalVectorExpressionGrammar)), ItemAttribute.GetDescription(typeof(FullFunctionalVectorExpressionGrammar))) {
    3839      Initialize();
    3940    }
    4041
    4142    public override IDeepCloneable Clone(Cloner cloner) {
    42       return new FullFunctionalExpressionGrammar(this, cloner);
     43      return new FullFunctionalVectorExpressionGrammar(this, cloner);
    4344    }
    4445
    … …  
    4849      var mul = new Multiplication();
    4950      var div = new Division();
    50       var aq = new AnalyticQuotient();
    51       var mean = new Average();
     51
    5252      var sin = new Sine();
    5353      var cos = new Cosine();
    5454      var tan = new Tangent();
     55
    5556      var log = new Logarithm();
    56       var abs = new Absolute();
    57       var tanh = new HyperbolicTangent();
    58       var pow = new Power();
    59       pow.InitialFrequency = 0.0;
    60       var square = new Square();
    61       square.InitialFrequency = 0.0;
    62       var cube = new Cube();
    63       cube.InitialFrequency = 0.0;
    64       var root = new Root();
    65       root.InitialFrequency = 0.0;
    66       var sqrt = new SquareRoot();
    67       sqrt.InitialFrequency = 0.0;
    68       var cubeRoot = new CubeRoot();
    69       cubeRoot.InitialFrequency = 0.0;
    70       var airyA = new AiryA();
    71       airyA.InitialFrequency = 0.0;
    72       var airyB = new AiryB();
    73       airyB.InitialFrequency = 0.0;
    74       var bessel = new Bessel();
    75       bessel.InitialFrequency = 0.0;
    76       var cosineIntegral = new CosineIntegral();
    77       cosineIntegral.InitialFrequency = 0.0;
    78       var dawson = new Dawson();
    79       dawson.InitialFrequency = 0.0;
    80       var erf = new Erf();
    81       erf.InitialFrequency = 0.0;
    82       var expIntegralEi = new ExponentialIntegralEi();
    83       expIntegralEi.InitialFrequency = 0.0;
    84       var fresnelCosineIntegral = new FresnelCosineIntegral();
    85       fresnelCosineIntegral.InitialFrequency = 0.0;
    86       var fresnelSineIntegral = new FresnelSineIntegral();
    87       fresnelSineIntegral.InitialFrequency = 0.0;
    88       var gamma = new Gamma();
    89       gamma.InitialFrequency = 0.0;
    90       var hypCosineIntegral = new HyperbolicCosineIntegral();
    91       hypCosineIntegral.InitialFrequency = 0.0;
    92       var hypSineIntegral = new HyperbolicSineIntegral();
    93       hypSineIntegral.InitialFrequency = 0.0;
    94       var norm = new Norm();
    95       norm.InitialFrequency = 0.0;
    96       var psi = new Psi();
    97       psi.InitialFrequency = 0.0;
    98       var sineIntegral = new SineIntegral();
    99       sineIntegral.InitialFrequency = 0.0;
     57      var exp = new Exponential();
    10058
    101       var exp = new Exponential();
    102       var @if = new IfThenElse();
    103       var gt = new GreaterThan();
    104       var lt = new LessThan();
    105       var and = new And();
    106       var or = new Or();
    107       var not = new Not();
    108       var xor = new Xor();
    10959
    110       var timeLag = new TimeLag();
    111       timeLag.InitialFrequency = 0.0;
    112       var integral = new Integral();
    113       integral.InitialFrequency = 0.0;
    114       var derivative = new Derivative();
    115       derivative.InitialFrequency = 0.0;
     60      var pow = new Power { InitialFrequency = 0.0 };
     61      var root = new Root { InitialFrequency = 0.0 };
     62      var square = new Square { InitialFrequency = 0.0 };
     63      var sqrt = new SquareRoot { InitialFrequency = 0.0 };
     64      var cube = new Cube { InitialFrequency = 0.0 };
     65      var cubeRoot = new CubeRoot { InitialFrequency = 0.0 };
    11666
    117       var variableCondition = new VariableCondition();
    118       variableCondition.InitialFrequency = 0.0;
    119 
    120       var constant = new Constant();
    121       constant.MinValue = -20;
    122       constant.MaxValue = 20;
    123       var variableSymbol = new HeuristicLab.Problems.DataAnalysis.Symbolic.Variable();
     67      var constant = new Constant { MinValue = -20, MaxValue = 20 };
     68      var variable = new Variable();
    12469      var binFactorVariable = new BinaryFactorVariable();
    12570      var factorVariable = new FactorVariable();
    126       var laggedVariable = new LaggedVariable();
    127       laggedVariable.InitialFrequency = 0.0;
    128       var autoregressiveVariable = new AutoregressiveTargetVariable();
    129       autoregressiveVariable.InitialFrequency = 0.0;
    130       autoregressiveVariable.Enabled = false;
     71      var vectorVariable = new Variable() { Name = "Vector Variable" };
    13172
    132       var allSymbols = new List<Symbol>() { add, sub, mul, div, aq, mean, abs, sin, cos, tan, log, square, cube, pow, sqrt, cubeRoot, root, exp, tanh,
    133         airyA, airyB, bessel, cosineIntegral, dawson, erf, expIntegralEi, fresnelCosineIntegral, fresnelSineIntegral, gamma, hypCosineIntegral, hypSineIntegral, norm, psi, sineIntegral,
    134         @if, gt, lt, and, or, not,xor, timeLag, integral, derivative, constant, variableSymbol, binFactorVariable, factorVariable, laggedVariable,autoregressiveVariable, variableCondition };
    135       var unaryFunctionSymbols = new List<Symbol>() { abs, square, sqrt, cube, cubeRoot, sin, cos, tan, log, exp, tanh, not, timeLag, integral, derivative,
    136         airyA, airyB, bessel, cosineIntegral, dawson, erf, expIntegralEi, fresnelCosineIntegral, fresnelSineIntegral, gamma, hypCosineIntegral, hypSineIntegral, norm, psi, sineIntegral
     73      var sum = new Sum();
     74      var mean = new Average() { Name = "Mean" };
     75
     76
     77      var allSymbols = new List<Symbol>() {
     78        add, sub, mul, div,
     79        sin, cos, tan,
     80        log, exp,
     81        square, sqrt, cube, cubeRoot, pow, root,
     82        constant, variable, binFactorVariable, factorVariable, vectorVariable,
     83        sum, mean
     84      };
     85      var unaryFunctionSymbols = new List<Symbol>() {
     86        sin, cos, tan,
     87        log, exp
    13788      };
    13889
    139       var binaryFunctionSymbols = new List<Symbol>() { pow, root, gt, lt, aq, variableCondition };
    140       var ternarySymbols = new List<Symbol>() { add, sub, mul, div, mean, and, or, xor };
    141       var terminalSymbols = new List<Symbol>() { variableSymbol, binFactorVariable, factorVariable, constant, laggedVariable, autoregressiveVariable };
     90      var binaryFunctionSymbols = new List<Symbol>() { pow, root };
     91      var ternarySymbols = new List<Symbol>() { add, sub, mul, div };
     92      var terminalSymbols = new List<Symbol>() { variable, binFactorVariable, factorVariable, vectorVariable, constant };
     93
     94      var aggregationSymbols = new List<Symbol>() { sum, mean };
    14295
    14396      foreach (var symb in allSymbols)
    … …  
    156109        SetSubtreeCount(terminalSymbol, 0, 0);
    157110      }
    158 
    159       SetSubtreeCount(@if, 3, 3);
     111      foreach (var aggrSymb in aggregationSymbols) {
     112        SetSubtreeCount(aggrSymb, 1, 1);
     113      }
    160114
    161115
    … …  
    172126      }
    173127    }
     128
     129    public override void ConfigureVariableSymbols(IDataAnalysisProblemData problemData) {
     130      base.ConfigureVariableSymbols(problemData);
     131
     132      var dataset = problemData.Dataset;
     133      foreach (var varSymbol in Symbols.OfType<VariableBase>().Where(sym => sym.Name == "Variable")) {
     134        if (!varSymbol.Fixed) {
     135          varSymbol.AllVariableNames = problemData.InputVariables.Select(x => x.Value).Where(x => dataset.VariableHasType<double>(x));
     136          varSymbol.VariableNames = problemData.AllowedInputVariables.Where(x => dataset.VariableHasType<double>(x));
     137        }
     138      }
     139      foreach (var varSymbol in Symbols.OfType<VariableBase>().Where(sym => sym.Name == "Vector Variable")) {
     140        if (!varSymbol.Fixed) {
     141          varSymbol.AllVariableNames = problemData.InputVariables.Select(x => x.Value).Where(x => dataset.VariableHasType<DoubleVector>(x));
     142          varSymbol.VariableNames = problemData.AllowedInputVariables.Where(x => dataset.VariableHasType<DoubleVector>(x));
     143        }
     144      }
     145    }
    174146  }
    175147}
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