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Changeset 5586


Ignore:
Timestamp:
03/02/11 00:52:18 (13 years ago)
Author:
mkommend
Message:

#1418: Adapated DataAnalysisProblemData as well as RegressionProblemData to use parameters.

Location:
branches/DataAnalysis Refactoring
Files:
9 edited

Legend:

Unmodified
Added
Removed

  • branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectiveMeanSquaredErrorTreeSizeEvaluator.cs

    r5549 r5586  
    5353    public static double[] Calculate(ISymbolicDataAnalysisTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
    5454      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
    55       IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
     55      IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable.Value, rows);
    5656      IEnumerable<double> boundedEstimationValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
    5757      double mse = OnlineMeanSquaredErrorEvaluator.Calculate(originalValues, boundedEstimationValues);

  • branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs

    r5551 r5586  
    5353    public static double[] Calculate(ISymbolicDataAnalysisTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
    5454      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
    55       IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
     55      IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable.Value, rows);
    5656      double r2 = OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, estimatedValues);
    5757      return new double[2] { r2, solution.Length };

  • branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveMeanSquaredErrorEvaluator.cs

    r5548 r5586  
    5353    public static double Calculate(ISymbolicDataAnalysisTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
    5454      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
    55       IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
     55      IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable.Value, rows);
    5656      IEnumerable<double> boundedEstimationValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
    5757      return OnlineMeanSquaredErrorEvaluator.Calculate(originalValues, boundedEstimationValues);

  • branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs

    r5551 r5586  
    5353    public static double Calculate(ISymbolicDataAnalysisTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, IRegressionProblemData problemData, IEnumerable<int> rows) {
    5454      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
    55       IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
     55      IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable.Value, rows);
    5656      return OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, estimatedValues);
    5757    }

  • branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisEvaluator.cs

    r5559 r5586  
    125125      if (count == 0) count = 1;
    126126      return RandomEnumerable.SampleRandomNumbers(seed, SamplesEnd.Value, SamplesStart.Value, count)
    127         .Where(i => i < ProblemDataParameter.ActualValue.TestPartitionStart || ProblemDataParameter.ActualValue.TestPartitionEnd <= i);
     127        .Where(i => i < ProblemDataParameter.ActualValue.TestPartitionStart.Value || ProblemDataParameter.ActualValue.TestPartitionEnd.Value <= i);
    128128    }
    129129  }

  • branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/DataAnalysisProblemData.cs

    r5565 r5586  
    2323using System.Collections.Generic;
    2424using System.Linq;
     25using HeuristicLab.Collections;
    2526using HeuristicLab.Common;
    2627using HeuristicLab.Core;
     28using HeuristicLab.Data;
     29using HeuristicLab.Parameters;
    2730using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
    2831
    2932namespace HeuristicLab.Problems.DataAnalysis {
    3033  [StorableClass]
    31   public abstract class DataAnalysisProblemData : NamedItem, IDataAnalysisProblemData {
     34  public abstract class DataAnalysisProblemData : ParameterizedNamedItem, IDataAnalysisProblemData {
     35    private const string DatasetParameterName = "Dataset";
     36    private const string InputVariablesParameterName = "InputVariables";
     37    private const string TrainingPartitionStartParameterName = "TrainingPartitionStart";
     38    private const string TrainingPartitionEndParameterName = "TrainingPartitionEnd";
     39    private const string TestPartitionStartParameterName = "TestPartitionStart";
     40    private const string TestPartitionEndParameterName = "TestPartitionEnd";
     41
     42    #region parameter properites
     43    public IValueParameter<Dataset> DatasetParameter {
     44      get { return (IValueParameter<Dataset>)Parameters[DatasetParameterName]; }
     45    }
     46    public IFixedValueParameter<ICheckedItemCollection<StringValue>> InputVariablesParameter {
     47      get { return (IFixedValueParameter<ICheckedItemCollection<StringValue>>)Parameters[InputVariablesParameterName]; }
     48    }
     49    public IFixedValueParameter<IntValue> TrainingPartitionStartParameter {
     50      get { return (IFixedValueParameter<IntValue>)Parameters[TrainingPartitionStartParameterName]; }
     51    }
     52    public IFixedValueParameter<IntValue> TrainingPartitionEndParameter {
     53      get { return (IFixedValueParameter<IntValue>)Parameters[TrainingPartitionEndParameterName]; }
     54    }
     55    public IFixedValueParameter<IntValue> TestPartitionStartParameter {
     56      get { return (IFixedValueParameter<IntValue>)Parameters[TestPartitionStartParameterName]; }
     57    }
     58    public IFixedValueParameter<IntValue> TestPartitionEndParameter {
     59      get { return (IFixedValueParameter<IntValue>)Parameters[TestPartitionEndParameterName]; }
     60    }
     61    #endregion
     62
    3263    #region propeties
    33     [Storable]
    34     private Dataset dataset;
    3564    public Dataset Dataset {
    36       get { return dataset; }
     65      get { return DatasetParameter.Value; }
     66      set { DatasetParameter.Value = value; }
     67    }
     68    public ICheckedItemCollection<StringValue> InputVariables {
     69      get { return InputVariablesParameter.Value; }
     70    }
     71    public IEnumerable<string> AllowedInputVariables {
     72      get { return InputVariables.CheckedItems.Select(x => x.Value); }
    3773    }
    3874
    39     [Storable]
    40     private HashSet<string> allowedInputVariables;
    41     public IEnumerable<string> AllowedInputVariables {
    42       get { return allowedInputVariables; }
     75    public IntValue TrainingPartitionStart {
     76      get { return TrainingPartitionStartParameter.Value; }
    4377    }
    44 
    45     [Storable]
    46     private int trainingPartitionStart;
    47     public int TrainingPartitionStart {
    48       get { return trainingPartitionStart; }
    49       set {
    50         if (0 < value || value > dataset.Rows)
    51           throw new ArgumentException(string.Format("The training partition start must be between 0 and the number of rows of the dataset ({0})", dataset.Rows));
    52         if (trainingPartitionStart != value) {
    53           trainingPartitionStart = value;
    54           OnChanged();
    55         }
    56       }
     78    public IntValue TrainingPartitionEnd {
     79      get { return TrainingPartitionEndParameter.Value; }
    5780    }
    58     [Storable]
    59     private int trainingPartitionEnd;
    60     public int TrainingPartitionEnd {
    61       get { return trainingPartitionEnd; }
    62       set {
    63         if (0 < value || value > dataset.Rows)
    64           throw new ArgumentException(string.Format("The training partition end must be between 0 and the number of rows of the dataset ({0})", dataset.Rows));
    65         if (trainingPartitionEnd != value) {
    66           trainingPartitionEnd = value;
    67           OnChanged();
    68         }
    69       }
     81    public IntValue TestPartitionStart {
     82      get { return TestPartitionStartParameter.Value; }
    7083    }
    71 
    72     [Storable]
    73     private int testPartitionStart;
    74     public int TestPartitionStart {
    75       get { return testPartitionStart; }
    76       set {
    77         if (0 < value || value > dataset.Rows)
    78           throw new ArgumentException(string.Format("The test partition start must be between 0 and the number of rows of the dataset ({0})", dataset.Rows));
    79         if (testPartitionStart != value) {
    80           testPartitionStart = value;
    81           OnChanged();
    82         }
    83       }
    84     }
    85     [Storable]
    86     private int testPartitionEnd;
    87     public int TestPartitionEnd {
    88       get { return testPartitionEnd; }
    89       set {
    90         if (0 < value || value > dataset.Rows)
    91           throw new ArgumentException(string.Format("The test partition end must be between 0 and the number of rows of the dataset ({0})", dataset.Rows));
    92         if (testPartitionEnd != value) {
    93           testPartitionEnd = value;
    94           OnChanged();
    95         }
    96       }
     84    public IntValue TestPartitionEnd {
     85      get { return TestPartitionEndParameter.Value; }
    9786    }
    9887
    9988    public IEnumerable<int> TrainingIndizes {
    10089      get {
    101         return Enumerable.Range(TrainingPartitionStart, TrainingPartitionEnd - TrainingPartitionStart)
    102                          .Where(i => i >= 0 && i < Dataset.Rows && (i < TestPartitionStart || TestPartitionEnd <= i));
     90        return Enumerable.Range(TrainingPartitionStart.Value, TrainingPartitionEnd.Value - TrainingPartitionStart.Value)
     91                         .Where(i => i >= 0 && i < Dataset.Rows && (i < TestPartitionStart.Value || TestPartitionEnd.Value <= i));
    10392      }
    10493    }
    10594    public IEnumerable<int> TestIndizes {
    10695      get {
    107         return Enumerable.Range(TestPartitionStart, TestPartitionEnd - TestPartitionStart)
     96        return Enumerable.Range(TestPartitionStart.Value, TestPartitionEnd.Value - TestPartitionStart.Value)
    10897           .Where(i => i >= 0 && i < Dataset.Rows);
    10998      }
    … …  
    122111        throw new ArgumentException("All allowed input variables must be present in the dataset.");
    123112
    124       this.dataset = dataset;
    125       this.allowedInputVariables = new HashSet<string>(allowedInputVariables);
    126       trainingPartitionStart = 0;
    127       trainingPartitionEnd = dataset.Rows / 2;
    128       testPartitionStart = dataset.Rows / 2;
    129       testPartitionEnd = dataset.Rows;
     113      var inputVariables = new CheckedItemCollection<StringValue>(dataset.VariableNames.Select(x => new StringValue(x)));
     114      foreach (StringValue x in inputVariables)
     115        inputVariables.SetItemCheckedState(x, allowedInputVariables.Contains(x.Value));
     116
     117      int trainingPartitionStart = 0;
     118      int trainingPartitionEnd = dataset.Rows / 2;
     119      int testPartitionStart = dataset.Rows / 2;
     120      int testPartitionEnd = dataset.Rows;
     121
     122      Parameters.Add(new ValueParameter<Dataset>(DatasetParameterName, "", dataset));
     123      Parameters.Add(new FixedValueParameter<ICheckedItemCollection<StringValue>>(InputVariablesParameterName, "", inputVariables.AsReadOnly()));
     124      Parameters.Add(new FixedValueParameter<IntValue>(TrainingPartitionStartParameterName, "", new IntValue(trainingPartitionStart)));
     125      Parameters.Add(new FixedValueParameter<IntValue>(TrainingPartitionEndParameterName, "", new IntValue(trainingPartitionEnd)));
     126      Parameters.Add(new FixedValueParameter<IntValue>(TestPartitionStartParameterName, "", new IntValue(testPartitionStart)));
     127      Parameters.Add(new FixedValueParameter<IntValue>(TestPartitionEndParameterName, "", new IntValue(testPartitionEnd)));
     128
     129      RegisterEventHandlers();
    130130    }
    131131
    132     public bool AddAllowedInputVariable(string inputVariable) {
    133       if (!Dataset.VariableNames.Contains(inputVariable))
    134         throw new ArgumentException("The allowed input variable must be present in the dataset.");
    135       if (allowedInputVariables.Contains(inputVariable)) return false;
     132    private void RegisterEventHandlers() {
     133      DatasetParameter.ValueChanged += new EventHandler(Parameter_ValueChanged);
     134      InputVariables.CheckedItemsChanged += new CollectionItemsChangedEventHandler<StringValue>(InputVariables_CheckedItemsChanged);
     135      TrainingPartitionStart.ValueChanged += new EventHandler(Parameter_ValueChanged);
     136      TrainingPartitionEnd.ValueChanged += new EventHandler(Parameter_ValueChanged);
     137      TestPartitionStart.ValueChanged += new EventHandler(Parameter_ValueChanged);
     138      TestPartitionEnd.ValueChanged += new EventHandler(Parameter_ValueChanged);
     139    }
    136140
    137       allowedInputVariables.Add(inputVariable);
    138       return true;
     141    private void InputVariables_CheckedItemsChanged(object sender, CollectionItemsChangedEventArgs<StringValue> e) {
     142      OnChanged();
    139143    }
    140     public bool RemoveAllowedInputVariable(string inputVariable) {
    141       if (!Dataset.VariableNames.Contains(inputVariable))
    142         throw new ArgumentException("The allowed input variable must be present in the dataset.");
    143       if (!allowedInputVariables.Contains(inputVariable)) return false;
    144 
    145       allowedInputVariables.Remove(inputVariable);
    146       return true;
     144    private void Parameter_ValueChanged(object sender, EventArgs e) {
     145      OnChanged();
    147146    }
    148147

  • branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataAnalysisProblemData.cs

    r5559 r5586  
    2323using System.Collections.Generic;
    2424using HeuristicLab.Core;
     25using HeuristicLab.Data;
    2526
    2627namespace HeuristicLab.Problems.DataAnalysis {
    27   public interface IDataAnalysisProblemData : INamedItem {
    28     Dataset Dataset { get; }
     28  public interface IDataAnalysisProblemData : IParameterizedNamedItem {
     29    Dataset Dataset { get; set; }
     30    ICheckedItemCollection<StringValue> InputVariables { get; }
    2931    IEnumerable<string> AllowedInputVariables { get; }
    3032
    31     bool AddAllowedInputVariable(string inputVariable);
    32     bool RemoveAllowedInputVariable(string inputVariable);
    33 
    34     int TrainingPartitionStart { get; set; }
    35     int TrainingPartitionEnd { get; set; }
    36     int TestPartitionStart { get; set; }
    37     int TestPartitionEnd { get; set; }
     33    IntValue TrainingPartitionStart { get; }
     34    IntValue TrainingPartitionEnd { get; }
     35    IntValue TestPartitionStart { get; }
     36    IntValue TestPartitionEnd { get; }
    3837
    3938    IEnumerable<int> TrainingIndizes { get; }

  • branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionProblemData.cs

    r5559 r5586  
    2020#endregion
    2121
     22using HeuristicLab.Data;
    2223namespace HeuristicLab.Problems.DataAnalysis {
    2324  public interface IRegressionProblemData : IDataAnalysisProblemData {
    24     string TargetVariable { get; set; }
     25    StringValue TargetVariable { get; }
    2526  }
    2627}

  • branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/RegressionProblemData.cs

    r5559 r5586  
    2020#endregion
    2121
    22 using System;
    2322using System.Collections.Generic;
    2423using System.IO;
    2524using System.Linq;
    2625using HeuristicLab.Common;
     26using HeuristicLab.Core;
     27using HeuristicLab.Data;
     28using HeuristicLab.Parameters;
    2729using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
    2830
    … …  
    3032  [StorableClass]
    3133  public sealed class RegressionProblemData : DataAnalysisProblemData, IRegressionProblemData {
     34    private const string TargetVariableParameterName = "TargetVariable";
    3235
    3336    #region default data
    … …  
    7275    #endregion
    7376
    74     #region propeties
    75     [Storable]
    76     private string targetVariable;
    77     public string TargetVariable {
    78       get { return targetVariable; }
    79       set {
    80         if (!Dataset.VariableNames.Contains(value))
    81           throw new ArgumentException(string.Format("The target variable {0} is not present in the dataset", value));
    82         if (targetVariable != value) {
    83           targetVariable = value;
    84           OnChanged();
    85         }
    86       }
     77    public IValueParameter<StringValue> TargetVariableParameter {
     78      get { return (IValueParameter<StringValue>)Parameters[TargetVariableParameterName]; }
    8779    }
    88     #endregion
     80    public StringValue TargetVariable {
     81      get { return TargetVariableParameter.Value; }
     82    }
     83
    8984
    9085    [StorableConstructor]
    … …  
    9994    public RegressionProblemData(Dataset dataset, IEnumerable<string> allowedInputVariables, string targetVariable)
    10095      : base(dataset, allowedInputVariables) {
    101       TargetVariable = targetVariable;
     96      Parameters.Add(new ConstrainedValueParameter<StringValue>("TargetVariable", new ItemSet<StringValue>(InputVariables), InputVariables.Where(x => x.Value == targetVariable).First()));
    10297    }
    10398
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