#include <itkSingleValuedNonLinearVnlOptimizer.h>
Inheritance diagram for itk::SingleValuedNonLinearVnlOptimizer:
It is an Adaptor class for optimizers provided by the vnl library
Definition at line 36 of file itkSingleValuedNonLinearVnlOptimizer.h.
|
Command observer that will interact with the ITK-VNL cost-function adaptor in order to generate iteration events. This will allow to overcome the limitation of VNL optimizers not offering callbacks for every iteration Definition at line 54 of file itkSingleValuedNonLinearVnlOptimizer.h. |
|
Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer. Definition at line 44 of file itkSingleValuedNonLinearVnlOptimizer.h. |
|
Reimplemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer. Definition at line 96 of file itkSingleValuedNonLinearVnlOptimizer.h. |
|
Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer. Definition at line 43 of file itkSingleValuedNonLinearVnlOptimizer.h. |
|
Standard class typedefs. Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer. Definition at line 41 of file itkSingleValuedNonLinearVnlOptimizer.h. |
|
Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer. Definition at line 42 of file itkSingleValuedNonLinearVnlOptimizer.h. |
|
|
|
|
|
Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue(). |
|
Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue(). |
|
Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue(). |
|
|
|
|
|
Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0. |
|
Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0. Definition at line 72 of file itkSingleValuedNonLinearVnlOptimizer.h. |
|
Run-time type information (and related methods). Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer. |
|
The purpose of this method is to get around the lack of const-correctness in VNL cost-functions and optimizers |
|
Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0. |
|
Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0. |
|
Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0. Definition at line 78 of file itkSingleValuedNonLinearVnlOptimizer.h. |
|
Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0. Definition at line 76 of file itkSingleValuedNonLinearVnlOptimizer.h. |
|
Print out internal state Reimplemented from itk::SingleValuedNonLinearOptimizer. Reimplemented in itk::AmoebaOptimizer, and itk::LBFGSOptimizer. |
|
Set the cost Function. This method has to be overloaded by derived classes because the CostFunctionAdaptor requires to know the number of parameters at construction time. This number of parameters is obtained at run-time from the itkCostFunction. As a consequence each derived optimizer should construct its own CostFunctionAdaptor when overloading this method Implemented in itk::AmoebaOptimizer, itk::ConjugateGradientOptimizer, and itk::LBFGSOptimizer. |
|
|
|
Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0. |
|
Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0. Definition at line 74 of file itkSingleValuedNonLinearVnlOptimizer.h. |