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ConjugateGradientMinimizer Class

Class ConjugateGradientMinimizer minimizes a multivariable function using the Polak-Ribiere variant of the Fletcher-Reeves conjugate gradient method.
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreMinimizerBase
    CenterSpace.NMath.CoreConjugateGradientMinimizer

Namespace: CenterSpace.NMath.Core
Assembly: NMath (in NMath.dll) Version: 7.4
Syntax
Copy
[SerializableAttribute]
public class ConjugateGradientMinimizer : MinimizerBase, 
	IMultiVariableDMinimizer, ICloneable

The ConjugateGradientMinimizer type exposes the following members.

Constructors
 NameDescription
Public methodConjugateGradientMinimizer Default constructor.
Public methodConjugateGradientMinimizer(Double) Constructs a ConjugateGradientMinimizer instance with the given error tolerance.
Public methodConjugateGradientMinimizer(Int32) Constructs a ConjugateGradientMinimizer instance with the given maximum number of iterations.
Public methodConjugateGradientMinimizer(Double, Int32) Constructs a ConjugateGradientMinimizer instance with the given maximum number of iterations.
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Properties
 NameDescription
Public propertyError Gets the error associated with the mimimum just computed.
(Inherited from MinimizerBase)
Public propertyIterations Gets the number of iterations used in the estimate of the mimimum just computed.
(Inherited from MinimizerBase)
Public propertyMaxIterations Gets and sets the maximum number of iterations used in computing minima estimates.
(Inherited from MinimizerBase)
Public propertyMaxIterationsMet Returns true if the minimum just computed stopped because the maximum number of iterations was reached; otherwise, false.
(Inherited from MinimizerBase)
Public propertyTolerance Gets and sets the error tolerance used in computing minima estimates.
(Inherited from MinimizerBase)
Public propertyToleranceMet Returns true if the minimum just computed stopped because the error tolerance was reached; otherwise, false.
(Inherited from MinimizerBase)
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Methods
 NameDescription
Public methodClone Creates a deep copy of self.
(Overrides MinimizerBaseClone)
Public methodMinimize(DoubleFunctional, DoubleVector) Minimizes the given function near the given starting point.
Public methodMinimize(MultiVariableFunction, MultiVariableFunction, DoubleVector)Obsolete.
Minimizes the given function near the given starting point, using the given array of partial derivatives.
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Fields
 NameDescription
Protected fielderror_The current error.
(Inherited from MinimizerBase)
Protected fielditer_The current number of iterations performed.
(Inherited from MinimizerBase)
Protected fieldmax_The maximum number of iterations.
(Inherited from MinimizerBase)
Protected fieldtolerance_The error tolerance.
(Inherited from MinimizerBase)
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Remarks
Gradients are calculated using the partial derivatives then chosen based on a direction that is conjugate to the old gradient and, insofar as possible, to all previous directions traversed.
Iteration stops when either the estimated error is less than a specified error tolerance, or a specified maximum number of iterations is reached.
See Also