#region License Information
/* HeuristicLab
* Copyright (C) 2002-2012 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 System;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.RealVectorEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Algorithms.GradientDescent {
[StorableClass]
[Item(Name = "LBFGS Initializer", Description = "Initializes the necessary data structures for the LM-BFGS algorithm.")]
public sealed class LbfgsInitializer : SingleSuccessorOperator {
private const string PointParameterName = "Point";
private const string StateParameterName = "State";
private const string IterationsParameterName = "Iterations";
private const string ApproximateGradientsParameterName = "ApproximateGradients";
#region Parameter Properties
// in
public ILookupParameter IterationsParameter {
get { return (ILookupParameter)Parameters[IterationsParameterName]; }
}
public ILookupParameter PointParameter {
get { return (ILookupParameter)Parameters[PointParameterName]; }
}
// out
public ILookupParameter StateParameter {
get { return (ILookupParameter)Parameters[StateParameterName]; }
}
public ILookupParameter ApproximateGradientsParameter {
get { return (ILookupParameter)Parameters[ApproximateGradientsParameterName]; }
}
#endregion
#region Properties
private RealVector Point { get { return PointParameter.ActualValue; } }
private IntValue Iterations { get { return IterationsParameter.ActualValue; } }
private BoolValue ApproximateGradients { get { return ApproximateGradientsParameter.ActualValue; } }
#endregion
[StorableConstructor]
private LbfgsInitializer(bool deserializing) : base(deserializing) { }
private LbfgsInitializer(LbfgsInitializer original, Cloner cloner) : base(original, cloner) { }
public LbfgsInitializer()
: base() {
// in
Parameters.Add(new LookupParameter(PointParameterName, "The initial point for the LM-BFGS algorithm."));
Parameters.Add(new LookupParameter(IterationsParameterName, "The maximal number of iterations for the LM-BFGS algorithm."));
Parameters.Add(new LookupParameter(ApproximateGradientsParameterName,
"Flag that indicates if gradients should be approximated."));
// out
Parameters.Add(new LookupParameter(StateParameterName, "The state of the LM-BFGS algorithm."));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new LbfgsInitializer(this, cloner);
}
public override IOperation Apply() {
double[] initialPoint = Point.ToArray();
int n = initialPoint.Length;
alglib.minlbfgs.minlbfgsstate state = new alglib.minlbfgs.minlbfgsstate();
if (ApproximateGradients.Value) {
alglib.minlbfgs.minlbfgscreatef(n, Math.Min(n, 10), initialPoint, 1E-5, state);
} else {
alglib.minlbfgs.minlbfgscreate(n, Math.Min(n, 10), initialPoint, state);
}
alglib.minlbfgs.minlbfgssetcond(state, 0.0, 0, 0, Iterations.Value);
alglib.minlbfgs.minlbfgssetxrep(state, true);
PointParameter.ActualValue = new RealVector(initialPoint);
StateParameter.ActualValue = new LbfgsState(state);
return base.Apply();
}
}
}