#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
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 SelectedOperatorParameter {
get { return (ScopeTreeLookupParameter) Parameters["SelectedOperator"]; }
}
public ValueLookupParameter ResultsParameter {
get { return (ValueLookupParameter)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("SelectedOperator", "The selected operators in a population."));
Parameters.Add(new ValueLookupParameter("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 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;
}
}
}
}