source: branches/DataAnalysisService/HeuristicLab.ExperimentGeneration.DataAnalysis.ExperimentWizard/3.3/MediumAnalysisPage.cs @ 13806

using System;
using System.ComponentModel;
using System.Linq;
using System.Windows.Forms;
using HeuristicLab.Algorithms.DataAnalysis;
using HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm;
using HeuristicLab.Common;
using HeuristicLab.Data;
using HeuristicLab.Encodings.ParameterConfigurationTreeEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
namespace HeuristicLab.ExperimentGeneration.DataAnalysis.ExperimentWizard {
  public partial class MediumAnalysisPage : HeuristicLab.ExperimentGeneration.DataAnalysis.Wizard.WizardPage {
    private const int nrOfRepetitions = 10;
    private const string gaCrossover = "SubtreeSwappingCrossover";
    private const string gaMutator = "MultiSymbolicExpressionTreeManipulator";
    private const string gaSelector = "GenderSpecificSelection";

    private BackgroundWorker worker;

    private DataAnalysisWizardContext context;
    public DataAnalysisWizardContext Context {
      get { return context; }
    }

    public MediumAnalysisPage(DataAnalysisWizardContext context) {
      InitializeComponent();
      this.context = context;
      worker = new BackgroundWorker();
      worker.DoWork += new DoWorkEventHandler(GenerateExperimentsTask);
      worker.RunWorkerCompleted += new RunWorkerCompletedEventHandler(WorkerCompleted);
      worker.WorkerReportsProgress = true;
      worker.ProgressChanged += new ProgressChangedEventHandler(WorkerProgressChanged);
      worker.WorkerSupportsCancellation = true;
    }

    private void GenerateExperimentsTask(object sender, DoWorkEventArgs e) {
      DataAnalysisWizardContext c = e.Argument as DataAnalysisWizardContext;
      IProblem problem = c.Problem;
      if (worker.CancellationPending) {
        e.Cancel = true;
      } else {
        lblProgress.Invoke(new Action(() => { lblProgress.Text = "Generating Support Vector Regression Experiment ..."; }));
      }

      // SVR Experiment -------------------------------------------------------
      //Experiment svrExperiment = null;
      //if (!e.Cancel) {
      //  SupportVectorRegression svr = new SupportVectorRegression();
      //  svr.Problem = (IRegressionProblem)problem;
      //  ParameterConfigurationTree vc = new ParameterConfigurationTree(svr, problem);

      //  var nuRange = new DoubleValueRange(new DoubleValue(0.1), new DoubleValue(0.9), new DoubleValue(0.1));
      //  SetParameterRangeContraint(vc, "Nu", nuRange);

      //  var costRange = new DoubleValueFactorRange(new DoubleValue(0.03125), new DoubleValue(32768), new DoubleValue(4));
      //  SetParameterRangeContraint(vc, "Cost", costRange);

      //  var gammaRange = new DoubleValueFactorRange(new DoubleValue(6.10352E-05), new DoubleValue(64), new DoubleValue(4));
      //  SetParameterRangeContraint(vc, "Gamma", gammaRange);
      //  worker.ReportProgress(5);
      //  svrExperiment = vc.GenerateExperiment(svr);
      //}
      // ======================================================================

      if (worker.CancellationPending) {
        e.Cancel = true;
      } else {
        worker.ReportProgress(20);
        lblProgress.Invoke(new Action(() => { lblProgress.Text = "Generating Random Forest Regression Experiment ..."; }));
      }


      // RF Experiment --------------------------------------------------------
      //Experiment rfrExperiment = null;
      //if (!e.Cancel) {
      //  RandomForestRegression rfr = new RandomForestRegression();
      //  rfr.Problem = (IRegressionProblem)problem;
      //  ParameterConfigurationTree rfConfig = new ParameterConfigurationTree(rfr, problem);
      //  var rRange = new DoubleValueRange(new DoubleValue(0.1), new DoubleValue(0.7), new DoubleValue(0.1));
      //  SetParameterRangeContraint(rfConfig, "R", rRange);
      //  var treeRange = new IntValueRange(new IntValue(250), new IntValue(250), new IntValue(250));
      //  SetParameterRangeContraint(rfConfig, "Number of trees", treeRange);
      //  rfrExperiment = rfConfig.GenerateExperiment(rfr);
      //}
      // ======================================================================

      if (worker.CancellationPending) {
        e.Cancel = true;
      } else {
        worker.ReportProgress(40);
        lblProgress.Invoke(new Action(() => { lblProgress.Text = "Generating Neural Network Regression Experiment ..."; }));
      }


      // NN Experiment --------------------------------------------------------
      //Experiment nnrExperiment = null;
      //if (!e.Cancel) {
      //  NeuralNetworkRegression nnr = new NeuralNetworkRegression();
      //  nnr.Problem = (IRegressionProblem)problem;
      //  ParameterConfigurationTree nnrConfig = new ParameterConfigurationTree(nnr, problem);
      //  var decayRange = new DoubleValueFactorRange(new DoubleValue(0.001), new DoubleValue(100), new DoubleValue(10));
      //  SetParameterRangeContraint(nnrConfig, "Decay", decayRange);
      //  var nodesRange = new IntValueFactorRange(new IntValue(1), new IntValue(100), new IntValue(3));
      //  SetParameterRangeContraint(nnrConfig, "NodesInFirstHiddenLayer", nodesRange);
      //  nnrExperiment = nnrConfig.GenerateExperiment(nnr);
      //}
      // ======================================================================

      if (worker.CancellationPending) {
        e.Cancel = true;
      } else {
        worker.ReportProgress(60);
        lblProgress.Invoke(new Action(() => { lblProgress.Text = "Generating Offspring Selection Genetic Algorithm Experiment ..."; }));
      }

      // GP Experiment --------------------------------------------------------
      Experiment gpExperiment = new Experiment();
      if (!e.Cancel) {
        OffspringSelectionGeneticAlgorithm osga = new OffspringSelectionGeneticAlgorithm();
        var prob = new SymbolicRegressionSingleObjectiveProblem();
        prob.ProblemData = ((IRegressionProblem)problem).ProblemData;
        //prob.SolutionCreator = new MultiSymbolicDataAnalysisExpressionCreator();
        osga.Problem = prob;
        osga.ComparisonFactorLowerBound.Value = 1;
        osga.Crossover = osga.Problem.Operators.OfType<ICrossover>().FirstOrDefault(x => x.Name == gaCrossover);
        osga.MaximumEvaluatedSolutions.Value = 500000;
        osga.MaximumGenerations.Value = 100;
        osga.MutationProbability = new PercentValue(0.15);
        osga.Mutator = osga.Problem.Operators.OfType<IManipulator>().FirstOrDefault(x => x.Name == gaMutator);
        osga.PopulationSize.Value = 500;
        osga.Selector = osga.SelectorParameter.ValidValues.FirstOrDefault(x => x.Name == gaSelector);

        CrossValidation crossSmall = new CrossValidation();
        crossSmall.Algorithm = osga;
        BatchRun batchSmall = new BatchRun("small");
        batchSmall.Repetitions = nrOfRepetitions;
        batchSmall.Optimizer = crossSmall;

        CrossValidation crossMedium = (CrossValidation)crossSmall.Clone(new Cloner());
        var probMedium = (SymbolicRegressionSingleObjectiveProblem)prob.Clone(new Cloner());
        probMedium.MaximumSymbolicExpressionTreeDepth.Value = 12;
        probMedium.MaximumSymbolicExpressionTreeLength.Value = 125;
        crossMedium.Algorithm.Problem = probMedium;
        BatchRun batchMedium = new BatchRun("medium");
        batchMedium.Repetitions = nrOfRepetitions;
        batchMedium.Optimizer = crossMedium;

        CrossValidation crossLarge = (CrossValidation)crossSmall.Clone(new Cloner());
        var probLarge = (SymbolicRegressionSingleObjectiveProblem)prob.Clone(new Cloner());
        probLarge.MaximumSymbolicExpressionTreeDepth.Value = 17;
        probLarge.MaximumSymbolicExpressionTreeLength.Value = 250;
        crossLarge.Algorithm.Problem = probLarge;
        BatchRun batchLarge = new BatchRun("large");
        batchLarge.Repetitions = nrOfRepetitions;
        batchLarge.Optimizer = crossLarge;

        //Experiment gpExperiment = new Experiment();
        gpExperiment.Optimizers.Add(batchSmall);
        gpExperiment.Optimizers.Add(batchMedium);
        gpExperiment.Optimizers.Add(batchLarge);
      }
      // ======================================================================
      if (worker.CancellationPending) {
        e.Cancel = true;
      } else {
        worker.ReportProgress(80);
        lblProgress.Invoke(new Action(() => { lblProgress.Text = "Packing Data Analysis Experiment ..."; }));
      }

      Experiment experiment = new Experiment("Data Analysis Experiment");
      if (!e.Cancel) {
        //Experiment experiment = new Experiment("Data Analysis Experiment");
        //experiment.Optimizers.Add(svrExperiment);
        //experiment.Optimizers.Add(rfrExperiment);
        //experiment.Optimizers.Add(nnrExperiment);
        experiment.Optimizers.Add(gpExperiment);
      }

      if (worker.CancellationPending) {
        e.Cancel = true;
      } else {
        worker.ReportProgress(100);
        lblProgress.Invoke(new Action(() => { lblProgress.Text = "Experiment generation completed"; }));
      }

      e.Result = experiment;
    }

    private void SetParameterRangeContraint(ParameterConfigurationTree pct, string parameterName, IRange rangeContraint) {
      var pc = pct.AlgorithmConfiguration.ParameterConfigurations.Where(x => x.ParameterName == parameterName).SingleOrDefault();
      pc.Optimize = true;
      var vc = (RangeValueConfiguration)pc.ValueConfigurations.First();
      vc.Optimize = true;
      vc.RangeConstraint = rangeContraint;

    }

    private void WorkerProgressChanged(object sender, ProgressChangedEventArgs e) {
      progressBar1.Value = e.ProgressPercentage;
    }

    private void WorkerCompleted(object sender, RunWorkerCompletedEventArgs e) {
      if (e.Error != null) {
        SetWizardButton(Wizard.WizardButtons.Back);
        MessageBox.Show(e.Error.Message, "Error occurred while generating experiments", MessageBoxButtons.OK, MessageBoxIcon.Error);
      } else if (e.Cancelled) {
        // nothing to do here ...
      } else {
        SetWizardButton(Wizard.WizardButtons.Next);
        Experiment experiment = (Experiment)e.Result;
        context.Experiment = experiment;
      }
    }

    private void MediumAnalysisPage_WizardBack(object sender, Wizard.WizardPageEventArgs e) {
      e.NewPage = "SelectAnalysisPage";
    }

    private void MediumAnalysisPage_SetActive(object sender, System.ComponentModel.CancelEventArgs e) {
      SetWizardButton(Wizard.WizardButtons.None);
      worker.RunWorkerAsync(context);
    }

    private void MediumAnalysisPage_WizardCancel(object sender, CancelEventArgs e) {
      worker.CancelAsync();
    }
  }
}