source: branches/HeuristicLab.Problems.BioBoost/HeuristicLab.Problems.BioBoost/3.3/Analysis/MultiOperatorUsageAnalyzer.cs @ 13069

using HeuristicLab.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using System.Linq;

namespace HeuristicLab.BioBoost.Analysis {

  [Item("MultiOperatorUsageAnalyzer", "An operator for analyzing utilization of different choices of a multi manipulation operatoutilization of different choices of a multi manipulation operator.")]
  [StorableClass]
  public class MultiOperatorUsageAnalyzer : SingleSuccessorOperator, IAnalyzer {

    public bool EnabledByDefault { get { return false; } }

    #region Parameters
    public ScopeTreeLookupParameter<StringValue> SelectedOperatorParameter {
      get { return (ScopeTreeLookupParameter<StringValue>) Parameters["SelectedOperator"]; }
    } 
    public ValueLookupParameter<ResultCollection> ResultsParameter {
      get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
    }
    #endregion

    #region Construction & Cloning
    [StorableConstructor]
    protected MultiOperatorUsageAnalyzer(bool isDeserializing) : base(isDeserializing) {}
    protected MultiOperatorUsageAnalyzer(MultiOperatorUsageAnalyzer orig, Cloner cloner) : base(orig, cloner) {}
    public MultiOperatorUsageAnalyzer() {
      Parameters.Add(new ScopeTreeLookupParameter<StringValue>("SelectedOperator", "The selected operators in a population."));
      Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection where the best solution should be stored."));
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new MultiOperatorUsageAnalyzer(this, cloner);
    }
    #endregion

    public override IOperation Apply() {
      var operators = SelectedOperatorParameter.ActualValue;
      var table = GetOrCreateTable(SelectedOperatorParameter.ActualName + "Usages");
      AddValues(table, operators);
      var avgTable = GetOrCreateTable(SelectedOperatorParameter.ActualName + "Avg Usages");
      foreach (var row in table.Rows) {
        DataRow avgRow;
        if (!avgTable.Rows.TryGetValue(row.Name, out avgRow)) {
          avgRow = new DataRow(row.Name);
          avgRow.Values.AddRange(Enumerable.Repeat(0d, row.Values.Count - 1));
          avgTable.Rows.Add(avgRow);
        }
        avgRow.Values.Add(row.Values.Average());
      }
      return base.Apply();
    }

    private static void AddValues(DataTable table, ItemArray<StringValue> operators) {
      var n = operators.Length;
      var groups = operators
        .GroupBy(v => v.Value)
        .ToDictionary(g => g.Key, g => 1.0*g.Count()/n);
      var len = table.Rows.Count == 0 ? 0 : table.Rows.Max(r => r.Values.Count);
      foreach (var row in table.Rows) {
        var probability = 0d;
        if (groups.TryGetValue(row.Name, out probability))
          groups.Remove(row.Name);
        row.Values.Add(probability);
      }
      foreach (var newOp in groups) {
        var row = new DataRow(newOp.Key);
        row.Values.AddRange(Enumerable.Repeat(0d, len));
        row.Values.Add(newOp.Value);
        table.Rows.Add(row);
      }
    }

    private DataTable GetOrCreateTable(string tableName) {
      IResult result = null;
      if (ResultsParameter.ActualValue.TryGetValue(tableName, out result)) {
        return (DataTable)result.Value;
      } else {
        var table = new DataTable(tableName);
        ResultsParameter.ActualValue.Add(new Result(tableName, table));
        return table;
      }
    }
  }
}