private OptVariable[] GetVariables(double[] variablesArray)
{
OptVariable[] vars = new OptVariable[variablesArray.Length];
for (int i = 0; i < variablesArray.Length; i++)
{
vars[i] = new OptVariable(variablesArray[i]);
}
return(vars);
}
private OptSimplexVariable[] GetVariables(OptVariable[] variablesArray)
{
OptSimplexVariable[] vars = new OptSimplexVariable[variablesArray.Length];
for (int i = 0; i < variablesArray.Length; i++)
{
OptVariable var = variablesArray[i];
vars[i] = new OptSimplexVariable(var.Name, var.InitialGuess, var.Fixed);
}
return(vars);
}
private OptSimplexVariable[] GetVariables(OptVariable[] variablesArray)
{
OptSimplexVariable[] vars = new OptSimplexVariable[variablesArray.Length];
for (int i = 0; i < variablesArray.Length; i++)
{
OptVariable var = variablesArray[i];
vars[i] = new OptSimplexVariable(var.Name, var.InitialGuess, var.Fixed);
}
return vars;
}
/// <summary>
/// Computes the minimum point of a function of several variables.
/// </summary>
/// <param name="function">The function to minimize.</param>
/// <param name="variables">Array of size N containing the initial guess. N is the number of variables.</param>
/// <param name="initialStep">The initial change of the variables.</param>
/// <returns>Array containing the solution.</returns>
public double[] ComputeMin(OptMultivariateFunction function, OptVariable[] variables, double initialStep)
{
if (variables == null) return new double[0];
if (variables.Length == 0) return new double[0];
OptSimplexVariable[] simplexVariables = this.GetVariables(variables);
int maxFunc = this._MaxFunEvaluations;
return this.GetMinimum(function, simplexVariables, initialStep, this._Tolerance, ref maxFunc);
}
private OptVariable[] GetVariables(double[] variablesArray)
{
OptVariable[] vars = new OptVariable[variablesArray.Length];
for (int i = 0; i < variablesArray.Length; i++)
{
vars[i] = new OptVariable(variablesArray[i]);
}
return vars;
}
/// <summary>
/// Computes the minimum point of a function of several variables.
/// </summary>
/// <param name="function">The function to minimize.</param>
/// <param name="gradient">A delegate that computes the gradient.</param>
/// <param name="variables">Array of size N containing the varaibles.</param>
/// <returns>Array containing the solution.</returns>
public double[] ComputeMin(OptMultivariateFunction function, OptMultivariateGradient gradient, OptVariable[] variables)
{
if (variables == null) return new double[0];
if (variables.Length == 0) return new double[0];
int maxFunc = this._MaxFunEvaluations;
this._TNDriver.ETA = this._SearchSeverity;
this._TNDriver.STEPMX = this._MaximunStep;
double[] minimum = this._TNDriver.ComputeMin(function, gradient, variables, this._Tolerance, this._Accuracy, ref maxFunc);
this._FunEvaluations = maxFunc;
return minimum;
}
/// <summary>
/// Computes the minimum point of a function of several variables.
/// </summary>
/// <param name="function">The function to minimize.</param>
/// <param name="gradient">A delegate that computes the gradient.</param>
/// <param name="variables">Array of size N containing the varaibles.</param>
/// <returns>Array containing the solution.</returns>
public double[] ComputeMin(OptMultivariateFunction function, OptMultivariateGradient gradient, OptVariable[] variables)
{
if (variables == null) return new double[0];
if (variables.Length == 0) return new double[0];
int maxFunc = this._MaxFunEvaluations;
double[] minimum = this._Driver.ComputeMin(function, gradient, variables, this._Tolerance, this._AccuracyFactor, ref maxFunc);
this._FunEvaluations = maxFunc;
return minimum;
}