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Dwsim / data /DWSIM.Math.SwarmOps /Problems /CurveFittingLin.cs
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/// ------------------------------------------------------
/// SwarmOps - Numeric and heuristic optimization for C#
/// Copyright (C) 2003-2011 Magnus Erik Hvass Pedersen.
/// Please see the file license.txt for license details.
/// SwarmOps on the internet: http://www.Hvass-Labs.org/
/// ------------------------------------------------------
using System.Diagnostics;
namespace SwarmOps.Problems
{
/// <summary>
/// Curve-fitting to the linear curve f(x) = A*x + B.
/// This is meant as an example, you will want to use
/// linear regression instead for real applications.
/// </summary>
public class CurveFittingLin : CurveFitting
{
#region Constructors.
/// <summary>
/// Create the object.
/// </summary>
/// <param name="x">X-axis values.</param>
/// <param name="y">Y-axis values, curve to be fitted.</param>
/// <param name="minA">Minimum value for A parameter.</param>
/// <param name="maxA">Maximum value for A parameter.</param>
/// <param name="minB">Minimum value for B parameter.</param>
/// <param name="maxB">Maximum value for B parameter.</param>
public CurveFittingLin(
double[] x, double[] y,
double minA, double maxA,
double minB, double maxB)
: base(x, y)
{
_lowerBound = new double[] { minA, minB };
_lowerInit = _lowerBound;
_upperBound = new double[] { maxA, maxB };
_upperInit = _upperBound;
}
#endregion
#region Get and set parameters.
/// <summary>
/// Get the A parameter.
/// </summary>
public double GetA(double[] parameters)
{
return parameters[0];
}
/// <summary>
/// Set the A parameter.
/// </summary>
public void SetA(ref double[] parameters, double a)
{
parameters[0] = a;
}
/// <summary>
/// Get the B parameter.
/// </summary>
public double GetB(double[] parameters)
{
return parameters[1];
}
/// <summary>
/// Set the B parameter.
/// </summary>
public void SetB(ref double[] parameters, double b)
{
parameters[1] = b;
}
#endregion
#region Base-class overrides, Problem.
/// <summary>
/// Name of the optimization problem.
/// </summary>
public override string Name
{
get { return "CurveFittingLinear"; }
}
/// <summary>
/// Dimensionality of the optimization problem.
/// </summary>
public override int Dimensionality
{
get { return 2; }
}
/// <summary>
/// Threshold for an acceptable fitness value.
/// </summary>
public override double AcceptableFitness
{
get
{
return 0.01;
}
}
double[] _lowerBound;
/// <summary>
/// Lower boundary for the search-space.
/// </summary>
public override double[] LowerBound
{
get { return _lowerBound; }
}
double[] _upperBound;
/// <summary>
/// Upper boundary for the search-space.
/// </summary>
public override double[] UpperBound
{
get { return _upperBound; }
}
double[] _lowerInit;
/// <summary>
/// Lower initialization boundary.
/// </summary>
public override double[] LowerInit
{
get { return _lowerInit; }
}
double[] _upperInit;
/// <summary>
/// Upper initialization boundary.
/// </summary>
public override double[] UpperInit
{
get { return _upperInit; }
}
string[] _parameterName = { "a", "b" };
/// <summary>
/// Array with names of parameters.
/// </summary>
public override string[] ParameterName
{
get { return _parameterName; }
}
/// <summary>
/// Has the gradient has been implemented?
/// </summary>
public override bool HasGradient
{
get { return true; }
}
/// <summary>
/// Compute the gradient of the fitness-function.
/// </summary>
/// <param name="parameters">Candidate solution.</param>
/// <param name="v">Array for holding the gradient.</param>
public override int Gradient(double[] parameters, ref double[] v)
{
Debug.Assert(parameters != null && parameters.Length == Dimensionality);
Debug.Assert(v != null && v.Length == Dimensionality);
Debug.Assert(X.Length == Y.Length);
// Get parameters.
double a = GetA(parameters);
double b = GetB(parameters);
double gradientA = 0;
double gradientB = 0;
for (int i = 0; i < X.Length; i++)
{
double x = X[i];
double y = Y[i];
gradientA += x * (2 * x * a + b - y);
gradientB += a * x + 2 * b - y;
}
SetA(ref v, gradientA);
SetB(ref v, gradientB);
return 0;
}
#endregion
#region Base-class overrides, CurveFitting
/// <summary>
/// Compute the value y given x using the curve-fitting function.
/// </summary>
/// <param name="parameters">Parameters for curve-fitting function.</param>
/// <param name="x">X-axis value.</param>
/// <returns>Computed Y-axis value.</returns>
public override double ComputeY(double[] parameters, double x)
{
double a = GetA(parameters);
double b = GetB(parameters);
return a * x + b;
}
#endregion
}
}