jube-fork/Accord.Math/Optimization/Unconstrained/OptimizationProgressEventHandler.cs

// Accord Math Library
// The Accord.NET Framework
// http://accord-framework.net
//
// Copyright © César Souza, 2009-2017
// cesarsouza at gmail.com
//
//    This library is free software; you can redistribute it and/or
//    modify it under the terms of the GNU Lesser General Public
//    License as published by the Free Software Foundation; either
//    version 2.1 of the License, or (at your option) any later version.
//
//    This library 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
//    Lesser General Public License for more details.
//
//    You should have received a copy of the GNU Lesser General Public
//    License along with this library; if not, write to the Free Software
//    Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
//

namespace Accord.Math.Optimization
{
    using System;

    /// <summary>
    ///   Optimization progress event arguments.
    /// </summary>
    public class OptimizationProgressEventArgs : EventArgs
    {
        /// <summary>
        ///   Gets the current iteration of the method.
        /// </summary>
        /// 
        public int Iteration { get; private set; }

        /// <summary>
        ///   Gets the number of function evaluations performed.
        /// </summary>
        /// 
        public int Evaluations { get; private set; }

        /// <summary>
        ///   Gets the current gradient of the function being optimized.
        /// </summary>
        /// 
        public double[] Gradient { get; private set; }

        /// <summary>
        ///   Gets the norm of the current <see cref="Gradient"/>.
        /// </summary>
        /// 
        public double GradientNorm { get; private set; }

        /// <summary>
        ///   Gets the current solution parameters for the problem.
        /// </summary>
        /// 
        public double[] Solution { get; private set; }

        /// <summary>
        ///   Gets the norm of the current <see cref="Solution"/>.
        /// </summary>
        /// 
        public double SolutionNorm { get; private set; }

        /// <summary>
        ///   Gets the value of the function to be optimized
        ///   at the current proposed <see cref="Solution"/>.
        /// </summary>
        /// 
        public double Value { get; private set; }

        /// <summary>
        ///   Gets the current step size.
        /// </summary>
        /// 
        public double Step { get; private set; }


        /// <summary>
        ///   Gets or sets a value indicating whether the
        ///   optimization process is about to terminate.
        /// </summary>
        /// 
        /// <value><c>true</c> if finished; otherwise, <c>false</c>.</value>
        /// 
        public bool Finished { get; private set; }

        /// <summary>
        ///   An user-defined value associated with this object.
        /// </summary>
        /// 
        public object Tag { get; set; }

        /// <summary>
        ///   Initializes a new instance of the <see cref="OptimizationProgressEventArgs"/> class.
        /// </summary>
        /// 
        /// <param name="iteration">The current iteration of the optimization method.</param>
        /// <param name="evaluations">The number of function evaluations performed.</param>
        /// <param name="gradient">The current gradient of the function.</param>
        /// <param name="gnorm">The norm of the current gradient</param>
        /// <param name="xnorm">The norm of the current parameter vector.</param>
        /// <param name="solution">The current solution parameters.</param>
        /// <param name="value">The value of the function evaluated at the current solution.</param>
        /// <param name="stp">The current step size.</param>
        /// <param name="finished"><c>True</c> if the method is about to terminate, <c>false</c> otherwise.</param>
        /// 
        public OptimizationProgressEventArgs(
            int iteration, int evaluations,
            double[] gradient, double gnorm,
            double[] solution, double xnorm,
            double value, double stp, bool finished)
        {
            if (gradient != null)
                this.Gradient = (double[])gradient.Clone();

            if (solution != null)
                this.Solution = (double[])solution.Clone();

            this.Value = value;
            this.GradientNorm = gnorm;
            this.SolutionNorm = xnorm;

            this.Iteration = iteration;
            this.Evaluations = evaluations;

            this.Finished = finished;
            this.Step = stp;
        }
    }
}