Changeset 17579


Ignore:
Timestamp:
05/30/20 22:00:12 (11 months ago)
Author:
mkommend
Message:

#2971: Merged branch into trunk.

Location:
trunk
Files:
17 edited
3 copied

Legend:

Unmodified
Added
Removed
  • trunk/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/Interfaces/ISymbolicRegressionEvaluator.cs

    r17180 r17579  
    1 using HEAL.Attic;
    2 #region License Information
     1#region License Information
    32/* HeuristicLab
    43 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     
    2019 */
    2120#endregion
    22 
     21using HEAL.Attic;
    2322
    2423namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
  • trunk/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/Interfaces/ISymbolicRegressionModel.cs

    r17180 r17579  
    1 using HEAL.Attic;
    2 #region License Information
     1#region License Information
    32/* HeuristicLab
    43 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     
    2120#endregion
    2221
     22using HEAL.Attic;
     23
    2324namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
    2425  [StorableType("a411e2b5-f926-41a6-b55b-1aef862db2fb")]
  • trunk/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/Interfaces/ISymbolicRegressionSolution.cs

    r17180 r17579  
    2222
    2323
     24
    2425namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
    2526  [StorableType("dff1a450-e958-454f-bf8e-6b763fdcaff3")]
  • trunk/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionSolution.cs

    r17180 r17579  
    1 #region License Information
     1#region License Information
    22/* HeuristicLab
    33 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     
    2121
    2222using System.Linq;
     23using HEAL.Attic;
    2324using HeuristicLab.Common;
    2425using HeuristicLab.Core;
     
    2627using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
    2728using HeuristicLab.Optimization;
    28 using HEAL.Attic;
    2929
    3030namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
     
    4747    private const string TestNaNEvaluationsResultName = "Test NaN Evaluations";
    4848
     49    private const string ModelBoundsResultName = "Model Bounds";
     50
    4951    public new ISymbolicRegressionModel Model {
    5052      get { return (ISymbolicRegressionModel)base.Model; }
     
    9597      private set { ((IntValue)EstimationLimitsResultCollection[TestNaNEvaluationsResultName].Value).Value = value; }
    9698    }
     99
     100    public IntervalCollection ModelBoundsCollection {
     101      get {
     102        if (!ContainsKey(ModelBoundsResultName)) return null;
     103        return (IntervalCollection)this[ModelBoundsResultName].Value;
     104      }
     105      private set {
     106        if (ContainsKey(ModelBoundsResultName)) {
     107          this[ModelBoundsResultName].Value = value;
     108        } else {
     109          Add(new Result(ModelBoundsResultName, "Results concerning the derivation of symbolic regression solution", value));
     110        }
     111
     112      }
     113    }
     114
     115
    97116
    98117    [StorableConstructor]
     
    118137      estimationLimitResults.Add(new Result(TestNaNEvaluationsResultName, "", new IntValue()));
    119138      Add(new Result(EstimationLimitsResultsResultName, "Results concerning the estimation limits of symbolic regression solution", estimationLimitResults));
     139
     140      if (IntervalInterpreter.IsCompatible(Model.SymbolicExpressionTree))
     141        Add(new Result(ModelBoundsResultName, "Results concerning the derivation of symbolic regression solution", new IntervalCollection()));
     142
    120143      RecalculateResults();
    121144    }
     
    139162        CalculateResults();
    140163      }
     164
     165      if (!ContainsKey(ModelBoundsResultName)) {
     166        if (IntervalInterpreter.IsCompatible(Model.SymbolicExpressionTree)) {
     167          Add(new Result(ModelBoundsResultName, "Results concerning the derivation of symbolic regression solution", new IntervalCollection()));
     168          CalculateResults();
     169        }
     170      }
    141171    }
    142172
     
    159189      TrainingNaNEvaluations = Model.Interpreter.GetSymbolicExpressionTreeValues(Model.SymbolicExpressionTree, ProblemData.Dataset, ProblemData.TrainingIndices).Count(double.IsNaN);
    160190      TestNaNEvaluations = Model.Interpreter.GetSymbolicExpressionTreeValues(Model.SymbolicExpressionTree, ProblemData.Dataset, ProblemData.TestIndices).Count(double.IsNaN);
     191
     192      //Check if the tree contains unknown symbols for the interval calculation
     193      if (IntervalInterpreter.IsCompatible(Model.SymbolicExpressionTree))
     194        ModelBoundsCollection = CalculateModelIntervals(this);
     195    }
     196
     197    private static IntervalCollection CalculateModelIntervals(ISymbolicRegressionSolution solution) {
     198      var intervalEvaluation = new IntervalCollection();
     199      var interpreter = new IntervalInterpreter();
     200      var problemData = solution.ProblemData;
     201      var model = solution.Model;
     202      var variableRanges = problemData.VariableRanges.GetReadonlyDictionary();
     203
     204      intervalEvaluation.AddInterval($"Target {problemData.TargetVariable}", new Interval(variableRanges[problemData.TargetVariable].LowerBound, variableRanges[problemData.TargetVariable].UpperBound));
     205      intervalEvaluation.AddInterval("Model", interpreter.GetSymbolicExpressionTreeInterval(model.SymbolicExpressionTree, variableRanges));
     206
     207      if (DerivativeCalculator.IsCompatible(model.SymbolicExpressionTree)) {
     208        foreach (var inputVariable in model.VariablesUsedForPrediction.OrderBy(v => v, new NaturalStringComparer())) {
     209          var derivedModel = DerivativeCalculator.Derive(model.SymbolicExpressionTree, inputVariable);
     210          var derivedResultInterval = interpreter.GetSymbolicExpressionTreeInterval(derivedModel, variableRanges);
     211
     212          intervalEvaluation.AddInterval(" ∂f/∂" + inputVariable, new Interval(derivedResultInterval.LowerBound, derivedResultInterval.UpperBound));
     213        }
     214      }
     215
     216      return intervalEvaluation;
    161217    }
    162218  }
  • trunk/HeuristicLab.Problems.DataAnalysis.Symbolic.Views/3.4/InteractiveSymbolicDataAnalysisSolutionSimplifierView.cs

    r17430 r17579  
    3535namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Views {
    3636  public abstract partial class InteractiveSymbolicDataAnalysisSolutionSimplifierView : AsynchronousContentView {
    37     private Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode> foldedNodes;
    38     private Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode> changedNodes;
    39     private Dictionary<ISymbolicExpressionTreeNode, double> nodeImpacts;
     37    private readonly Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode> foldedNodes = new Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode>();
     38    private readonly Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode> changedNodes = new Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode>();
     39    private readonly Dictionary<ISymbolicExpressionTreeNode, Interval> nodeIntervals = new Dictionary<ISymbolicExpressionTreeNode, Interval>();
     40    private readonly Dictionary<ISymbolicExpressionTreeNode, double> nodeImpacts = new Dictionary<ISymbolicExpressionTreeNode, double>();
    4041
    4142    private readonly ISymbolicDataAnalysisSolutionImpactValuesCalculator impactCalculator;
     
    4950    protected InteractiveSymbolicDataAnalysisSolutionSimplifierView(ISymbolicDataAnalysisSolutionImpactValuesCalculator impactCalculator) {
    5051      InitializeComponent();
    51       foldedNodes = new Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode>();
    52       changedNodes = new Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode>();
    53       nodeImpacts = new Dictionary<ISymbolicExpressionTreeNode, double>();
    5452      this.Caption = "Interactive Solution Simplifier";
    5553      this.impactCalculator = impactCalculator;
     
    173171    protected override void OnContentChanged() {
    174172      base.OnContentChanged();
    175       foldedNodes = new Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode>();
     173      foldedNodes.Clear();
     174      changedNodes.Clear();
     175      nodeIntervals.Clear();
     176      nodeImpacts.Clear();
    176177      UpdateView();
    177178      viewHost.Content = this.Content;
     
    205206          foldedNodes[pair.Key] = MakeConstantTreeNode(pair.Value);
    206207        }
    207 
    208         nodeImpacts = impactAndReplacementValues.ToDictionary(x => x.Key, x => x.Value.Item1);
     208       
     209        foreach (var pair in impactAndReplacementValues) {
     210          nodeImpacts[pair.Key] = pair.Value.Item1;
     211        }
     212
     213        if (IntervalInterpreter.IsCompatible(tree)) {
     214          var regressionProblemData = Content.ProblemData as IRegressionProblemData;
     215          if (regressionProblemData != null) {
     216            var interpreter = new IntervalInterpreter();
     217            var variableRanges = regressionProblemData.VariableRanges.GetReadonlyDictionary();
     218            IDictionary<ISymbolicExpressionTreeNode, Interval> intervals;
     219            interpreter.GetSymbolicExpressionTreeIntervals(tree, variableRanges, out intervals);
     220            foreach (var kvp in intervals) {
     221              nodeIntervals[kvp.Key] = kvp.Value;
     222            }
     223          }
     224        }
    209225      } finally {
    210226        progress.Finish();
     
    303319          }
    304320        }
    305         if (visualTree != null)
     321        if (visualTree != null) {
     322          if (nodeIntervals.ContainsKey(treeNode))
     323            visualTree.ToolTip += String.Format($"{Environment.NewLine}Intervals: [{nodeIntervals[treeNode].LowerBound:G5} ... {nodeIntervals[treeNode].UpperBound:G5}]");
    306324          if (changedNodes.ContainsKey(treeNode)) {
    307325            visualTree.LineColor = Color.DodgerBlue;
     
    309327            visualTree.LineColor = Color.DarkOrange;
    310328          }
     329        }
    311330      }
    312331      treeChart.RepaintNodes();
  • trunk/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Interpreter/IntervalInterpreter.cs

    r17180 r17579  
    2323using System.Collections.Generic;
    2424using System.Linq;
     25using HEAL.Attic;
    2526using HeuristicLab.Common;
    2627using HeuristicLab.Core;
    2728using HeuristicLab.Data;
    2829using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
    29 using HEAL.Attic;
    3030using HeuristicLab.Parameters;
    3131
     
    8080    }
    8181
    82     public Interval GetSymbolicExpressionTreeInterval(ISymbolicExpressionTree tree, IDictionary<string, Interval> variableRanges) {
     82    public Interval GetSymbolicExpressionTreeInterval(ISymbolicExpressionTree tree, IReadOnlyDictionary<string, Interval> variableRanges) {
    8383      lock (syncRoot) {
    8484        EvaluatedSolutions++;
     
    9797
    9898    public Interval GetSymbolicExpressionTreeIntervals(ISymbolicExpressionTree tree,
    99       IDictionary<string, Interval> variableRanges, out IDictionary<ISymbolicExpressionTreeNode, Interval> nodeIntervals) {
     99      IReadOnlyDictionary<string, Interval> variableRanges, out IDictionary<ISymbolicExpressionTreeNode, Interval> nodeIntervals) {
    100100      lock (syncRoot) {
    101101        EvaluatedSolutions++;
     
    124124
    125125
    126     private static Instruction[] PrepareInterpreterState(ISymbolicExpressionTree tree, IDictionary<string, Interval> variableRanges) {
     126    private static Instruction[] PrepareInterpreterState(ISymbolicExpressionTree tree, IReadOnlyDictionary<string, Interval> variableRanges) {
    127127      if (variableRanges == null)
    128128        throw new ArgumentNullException("No variablew ranges are present!", nameof(variableRanges));
     
    234234            break;
    235235          }
    236         case OpCodes.Power: {
    237             result = Evaluate(instructions, ref instructionCounter, nodeIntervals);
    238             for (int i = 1; i < currentInstr.nArguments; i++) {
    239               var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
    240               result = Interval.Power(result, argumentInterval);
    241             }
    242             break;
    243           }
    244236        case OpCodes.Square: {
    245237            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
     
    247239            break;
    248240          }
    249         case OpCodes.Root: {
    250             result = Evaluate(instructions, ref instructionCounter, nodeIntervals);
    251             for (int i = 1; i < currentInstr.nArguments; i++) {
    252               var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
    253               result = Interval.Root(result, argumentInterval);
    254             }
    255             break;
    256           }
    257241        case OpCodes.SquareRoot: {
    258242            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
    259243            result = Interval.SquareRoot(argumentInterval);
     244            break;
     245          }
     246        case OpCodes.Cube: {
     247            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
     248            result = Interval.Cube(argumentInterval);
     249            break;
     250          }
     251        case OpCodes.CubeRoot: {
     252            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
     253            result = Interval.CubicRoot(argumentInterval);
     254            break;
     255          }
     256        case OpCodes.Absolute: {
     257            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
     258            result = Interval.Absolute(argumentInterval);
     259            break;
     260          }
     261        case OpCodes.AnalyticQuotient: {
     262            result = Evaluate(instructions, ref instructionCounter, nodeIntervals);
     263            for (var i = 1; i < currentInstr.nArguments; i++) {
     264              var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
     265              result = Interval.AnalyticalQuotient(result, argumentInterval);
     266            }
     267
    260268            break;
    261269          }
     
    274282        from n in tree.Root.GetSubtree(0).IterateNodesPrefix()
    275283        where
     284          !(n.Symbol is Problems.DataAnalysis.Symbolic.Variable) &&
     285          !(n.Symbol is Constant) &&
    276286          !(n.Symbol is StartSymbol) &&
    277287          !(n.Symbol is Addition) &&
     
    284294          !(n.Symbol is Logarithm) &&
    285295          !(n.Symbol is Exponential) &&
    286           !(n.Symbol is Power) &&
    287296          !(n.Symbol is Square) &&
    288           !(n.Symbol is Root) &&
    289297          !(n.Symbol is SquareRoot) &&
    290           !(n.Symbol is Problems.DataAnalysis.Symbolic.Variable) &&
    291           !(n.Symbol is Constant)
     298          !(n.Symbol is Cube) &&
     299          !(n.Symbol is CubeRoot) &&
     300          !(n.Symbol is Absolute) &&
     301          !(n.Symbol is AnalyticQuotient)
    292302        select n).Any();
    293303      return !containsUnknownSyumbol;
  • trunk/HeuristicLab.Problems.DataAnalysis.Views/3.4/Controls/PartialDependencePlot.cs

    r17180 r17579  
    3636namespace HeuristicLab.Problems.DataAnalysis.Views {
    3737  public partial class PartialDependencePlot : UserControl, IPartialDependencePlot {
    38     private ModifiableDataset sharedFixedVariables; // used for syncronising variable values between charts
     38    private ModifiableDataset sharedFixedVariables; // used for synchronizing variable values between charts
    3939    private ModifiableDataset internalDataset; // holds the x values for each point drawn
    4040
     
    351351
    352352    private void RecalculateTrainingLimits(bool initializeAxisRanges) {
    353       trainingMin = solutions.Select(s => s.ProblemData.Dataset.GetDoubleValues(freeVariable, s.ProblemData.TrainingIndices).Where(x => !double.IsNaN(x)).Min()).Max();
    354       trainingMax = solutions.Select(s => s.ProblemData.Dataset.GetDoubleValues(freeVariable, s.ProblemData.TrainingIndices).Where(x => !double.IsNaN(x)).Max()).Min();
     353      //Set min and max to the interval ranges
     354      trainingMin = solutions.Select(s => s.ProblemData.VariableRanges.GetInterval(freeVariable).LowerBound).Max();
     355      trainingMax = solutions.Select(s => s.ProblemData.VariableRanges.GetInterval(freeVariable).UpperBound).Min();
    355356
    356357      if (initializeAxisRanges) {
     
    438439      chart.Palette = ChartColorPalette.None;
    439440
    440       // Add confidence interval series before its coresponding series for correct z index
     441      // Add confidence interval series before its corresponding series for correct z index
    441442      foreach (var solution in solutions) {
    442443        Series ciSeries;
  • trunk/HeuristicLab.Problems.DataAnalysis.Views/3.4/HeuristicLab.Problems.DataAnalysis.Views-3.4.csproj

    r16658 r17579  
    221221    <Compile Include="Interfaces\IDataPreprocessorStarter.cs" />
    222222    <Compile Include="Interfaces\IPartialDependencePlot.cs" />
     223    <Compile Include="IntervalCollectionView.cs">
     224      <SubType>UserControl</SubType>
     225    </Compile>
     226    <Compile Include="IntervalCollectionView.Designer.cs">
     227      <DependentUpon>IntervalCollectionView.cs</DependentUpon>
     228    </Compile>
    223229    <Compile Include="MenuItems\ChangeDataOfOptimizersMenuItem.cs" />
    224230    <Compile Include="MenuItems\ShrinkDataAnalysisRunsMenuItem.cs" />
  • trunk/HeuristicLab.Problems.DataAnalysis.Views/3.4/IntervalCollectionView.cs

    r17578 r17579  
    3636    }
    3737
    38     public DataGridView DataGridView {
     38    private DataGridView DataGridView {
    3939      get => dataGridView;
    4040    }
  • trunk/HeuristicLab.Problems.DataAnalysis/3.4/HeuristicLab.Problems.DataAnalysis-3.4.csproj

    r16788 r17579  
    140140    <Compile Include="Implementation\ConstantModel.cs" />
    141141    <Compile Include="Implementation\DataAnalysisModel.cs" />
    142     <Compile Include="Implementation\Interval.cs" />
     142    <Compile Include="Implementation\Interval\Interval.cs" />
     143    <Compile Include="Implementation\Interval\IntervalCollection.cs" />
    143144    <Compile Include="Implementation\Regression\ConfidenceBoundRegressionSolution.cs" />
    144145    <Compile Include="Implementation\Regression\ConstantRegressionModel.cs" />
  • trunk/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Interval/Interval.cs

  • trunk/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Regression/RegressionProblemData.cs

    r17180 r17579  
    1 #region License Information
     1#region License Information
    22/* HeuristicLab
    33 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
     
    2323using System.Collections.Generic;
    2424using System.Linq;
     25using HEAL.Attic;
    2526using HeuristicLab.Common;
    2627using HeuristicLab.Core;
    2728using HeuristicLab.Data;
    2829using HeuristicLab.Parameters;
    29 using HEAL.Attic;
    3030
    3131namespace HeuristicLab.Problems.DataAnalysis {
     
    3434  public class RegressionProblemData : DataAnalysisProblemData, IRegressionProblemData, IStorableContent {
    3535    protected const string TargetVariableParameterName = "TargetVariable";
     36    protected const string VariableRangesParameterName = "VariableRanges";
     37    protected const string IntervalConstraintsParameterName = "IntervalConstraints";
    3638    public string Filename { get; set; }
    3739
     
    9193      problemData.Parameters.Add(new FixedValueParameter<IntRange>(TestPartitionParameterName, "", (IntRange)new IntRange(0, 0).AsReadOnly()));
    9294      problemData.Parameters.Add(new ConstrainedValueParameter<StringValue>(TargetVariableParameterName, new ItemSet<StringValue>()));
     95      problemData.Parameters.Add(new FixedValueParameter<IntervalCollection>(VariableRangesParameterName, "", new IntervalCollection()));
    9396      emptyProblemData = problemData;
    9497    }
     
    98101      get { return (IConstrainedValueParameter<StringValue>)Parameters[TargetVariableParameterName]; }
    99102    }
     103
     104    public IFixedValueParameter<IntervalCollection> VariableRangesParameter => (IFixedValueParameter<IntervalCollection>)Parameters[VariableRangesParameterName];
     105
     106    public IntervalCollection VariableRanges {
     107      get => VariableRangesParameter.Value;
     108    }
     109
     110
    100111    public string TargetVariable {
    101112      get { return TargetVariableParameter.Value.Value; }
     
    125136    [StorableHook(HookType.AfterDeserialization)]
    126137    private void AfterDeserialization() {
     138      if (!Parameters.ContainsKey(VariableRangesParameterName)) {
     139        var intervalCollection = CalculateDatasetIntervals(this.Dataset);
     140        Parameters.Add(new FixedValueParameter<IntervalCollection>(VariableRangesParameterName, intervalCollection));
     141      }
    127142      RegisterParameterEvents();
    128143    }
     
    152167      var variables = InputVariables.Select(x => x.AsReadOnly()).ToList();
    153168      Parameters.Add(new ConstrainedValueParameter<StringValue>(TargetVariableParameterName, new ItemSet<StringValue>(variables), variables.Where(x => x.Value == targetVariable).First()));
     169      var intervalCollection = CalculateDatasetIntervals(this.Dataset);
     170      Parameters.Add(new FixedValueParameter<IntervalCollection>(VariableRangesParameterName, intervalCollection));
    154171      RegisterParameterEvents();
     172    }
     173
     174    private static IntervalCollection CalculateDatasetIntervals(IDataset dataset) {
     175      IntervalCollection intervalCollection = new IntervalCollection();
     176      foreach (var variable in dataset.DoubleVariables) {// intervals are only possible for double variables
     177        var variableInterval = Interval.GetInterval(dataset.GetDoubleValues(variable));
     178        intervalCollection.AddInterval(variable, variableInterval);
     179      }
     180
     181      return intervalCollection;
    155182    }
    156183
  • trunk/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataAnalysisModel.cs

    r17180 r17579  
    2525
    2626namespace HeuristicLab.Problems.DataAnalysis {
    27   [StorableType("f85ccf7a-7df5-431e-bc4d-be6f3c4c2338")]
    2827  /// <summary>
    2928  /// Interface for all data-analysis models (regression/classification/clustering).
    3029  /// <remarks>All methods and properties in in this interface must be implemented thread safely</remarks>
    3130  /// </summary>
     31  [StorableType("f85ccf7a-7df5-431e-bc4d-be6f3c4c2338")]
    3232  public interface IDataAnalysisModel : INamedItem {
    3333    IEnumerable<string> VariablesUsedForPrediction { get; }
  • trunk/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDataAnalysisProblem.cs

    r17180 r17579  
    3535  [StorableType("c2f6fcdd-ab62-4423-be75-01aa694df411")]
    3636  public interface IDataAnalysisProblem<T> : IDataAnalysisProblem
    37   where T : class, IDataAnalysisProblemData {
     37    where T : class, IDataAnalysisProblemData {
    3838    new IValueParameter<T> ProblemDataParameter { get; }
    3939    new T ProblemData { get; set; }
  • trunk/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IDependencyCalculator.cs

    r17180 r17579  
    2222using System;
    2323using System.Collections.Generic;
     24using HEAL.Attic;
    2425
    2526namespace HeuristicLab.Problems.DataAnalysis {
     27  [StorableType("3283B3FB-8467-4B99-9B6E-23BF3D1B8505")]
    2628  public interface IDependencyCalculator {
    2729    double Maximum { get; }
  • trunk/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/IOnlineCalculator.cs

    r17180 r17579  
    2222
    2323using System;
     24using HEAL.Attic;
     25
    2426namespace HeuristicLab.Problems.DataAnalysis {
    2527  [Flags]
     28  [StorableType("8A28DDA1-4814-4B77-9457-0EE930BE9C73")]
    2629  public enum OnlineCalculatorError {
    2730    /// <summary>
     
    3841    InsufficientElementsAdded = 2
    3942  }
     43
     44  [StorableType("119C8242-3EE7-4C34-A7AC-68ABF76EB11B")]
    4045  public interface IOnlineCalculator {
    4146    OnlineCalculatorError ErrorState { get; }
  • trunk/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionProblemData.cs

    r17180 r17579  
    2828    string TargetVariable { get; set; }
    2929
     30    IntervalCollection VariableRanges { get;}
     31
    3032    IEnumerable<double> TargetVariableValues { get; }
    3133    IEnumerable<double> TargetVariableTrainingValues { get; }
  • trunk/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/TimeSeriesPrognosis/IOnlineTimeSeriesCalculator.cs

    r17180 r17579  
    2222
    2323using System.Collections.Generic;
     24using HEAL.Attic;
    2425
    2526namespace HeuristicLab.Problems.DataAnalysis {
     27  [StorableType("7461AC5D-9D9A-4DCD-B32F-602260E58FFC")]
    2628  public interface IOnlineTimeSeriesCalculator {
    2729    OnlineCalculatorError ErrorState { get; }
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