itkMoreThuenteLineSearchOptimizer.h

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/*=========================================================================
 *
 *  Copyright UMC Utrecht and contributors
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *        http://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
 *
 *=========================================================================*/
 
#ifndef itkMoreThuenteLineSearchOptimizer_h
#define itkMoreThuenteLineSearchOptimizer_h
 
#include "itkLineSearchOptimizer.h"
 
namespace itk
{
class MoreThuenteLineSearchOptimizer : public LineSearchOptimizer
{
public:
  ITK_DISALLOW_COPY_AND_MOVE(MoreThuenteLineSearchOptimizer);
 
  using Self = MoreThuenteLineSearchOptimizer;
  using Superclass = LineSearchOptimizer;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;
 
  itkNewMacro(Self);
  itkTypeMacro(MoreThuenteLineSearchOptimizer, LineSearchOptimizer);
 
  using Superclass::MeasureType;
  using Superclass::ParametersType;
  using Superclass::DerivativeType;
  using Superclass::CostFunctionType;
 
  enum StopConditionType
  {
    StrongWolfeConditionsSatisfied,
    MetricError,
    MaximumNumberOfIterations,
    StepTooSmall,
    StepTooLarge,
    IntervalTooSmall,
    RoundingError,
    AscentSearchDirection,
    Unknown
  };
 
  void
  StartOptimization() override;
 
  virtual void
  StopOptimization();
 
  void
  SetInitialDerivative(const DerivativeType & derivative) override;
 
  void
  SetInitialValue(MeasureType value) override;
 
  void
  GetCurrentValueAndDerivative(MeasureType & value, DerivativeType & derivative) const override;
 
  void
  GetCurrentDerivative(DerivativeType & derivative) const override;
 
  MeasureType
  GetCurrentValue() const override;
 
  virtual double
  GetCurrentDirectionalDerivative() const;
 
  itkGetConstMacro(CurrentIteration, unsigned long);
  itkGetConstReferenceMacro(StopCondition, StopConditionType);
  itkGetConstMacro(SufficientDecreaseConditionSatisfied, bool);
  itkGetConstMacro(CurvatureConditionSatisfied, bool);
 
  itkGetConstMacro(MaximumNumberOfIterations, unsigned long);
  itkSetClampMacro(MaximumNumberOfIterations, unsigned long, 1, NumericTraits<unsigned long>::max());
 
  itkSetClampMacro(ValueTolerance, double, 0.0, NumericTraits<double>::max());
  itkGetConstMacro(ValueTolerance, double);
 
  itkSetClampMacro(GradientTolerance, double, 0.0, NumericTraits<double>::max());
  itkGetConstMacro(GradientTolerance, double);
 
  itkSetClampMacro(IntervalTolerance, double, 0.0, NumericTraits<double>::max());
  itkGetConstMacro(IntervalTolerance, double);
 
protected:
  MoreThuenteLineSearchOptimizer();
  ~MoreThuenteLineSearchOptimizer() override = default;
 
  void
  PrintSelf(std::ostream & os, Indent indent) const override;
 
  unsigned long     m_CurrentIteration{};
  bool              m_InitialDerivativeProvided{};
  bool              m_InitialValueProvided{};
  StopConditionType m_StopCondition{};
  bool              m_Stop{};
  bool              m_SufficientDecreaseConditionSatisfied{};
  bool              m_CurvatureConditionSatisfied{};
 
  virtual void
  GetInitialValueAndDerivative();
 
  virtual int
  CheckSettings();
 
  void
  InitializeLineSearch();
 
  virtual void
  UpdateIntervalMinimumAndMaximum();
 
  void
  BoundStep(double & step) const;
 
  virtual void
  PrepareForUnusualTermination();
 
  virtual void
  ComputeCurrentValueAndDerivative();
 
  virtual void
  TestConvergence(bool & stop);
 
  virtual void
  ComputeNewStepAndInterval();
 
  virtual void
  ForceSufficientDecreaseInIntervalWidth();
 
  virtual int
  SafeGuardedStep(double &     stx,
                  double &     fx,
                  double &     dx,
                  double &     sty,
                  double &     fy,
                  double &     dy,
                  double &     stp,
                  const double fp,
                  const double dp,
                  bool &       brackt,
                  const double stpmin,
                  const double stpmax) const;
 
  double m_step{};
  double m_stepx{};
  double m_stepy{};
  double m_stepmin{};
  double m_stepmax{};
 
  MeasureType m_f{}; // CurrentValue
  MeasureType m_fx{};
  MeasureType m_fy{};
  MeasureType m_finit{};
 
  DerivativeType m_g{};  // CurrentDerivative
  double         m_dg{}; // CurrentDirectionalDerivative
  double         m_dginit{};
  double         m_dgx{};
  double         m_dgy{};
  double         m_dgtest{};
 
  double m_width{};
  double m_width1{};
 
  bool m_brackt{};
  bool m_stage1{};
  bool m_SafeGuardedStepFailed{};
 
private:
  unsigned long m_MaximumNumberOfIterations{};
  double        m_ValueTolerance{};
  double        m_GradientTolerance{};
  double        m_IntervalTolerance{};
};
 
} // end namespace itk
 
/*                     SUBROUTINE MCSRCH */
 
/*     A slight modification of the subroutine CSRCH of More' and Thuente. */
/*     The changes are to allow reverse communication, and do not affect */
/*     the performance of the routine. */
 
/*     THE PURPOSE OF MCSRCH IS TO FIND A STEP WHICH SATISFIES */
/*     A SUFFICIENT DECREASE CONDITION AND A CURVATURE CONDITION. */
 
/*     AT EACH STAGE THE SUBROUTINE UPDATES AN INTERVAL OF */
/*     UNCERTAINTY WITH ENDPOINTS STX AND STY. THE INTERVAL OF */
/*     UNCERTAINTY IS INITIALLY CHOSEN SO THAT IT CONTAINS A */
/*     MINIMIZER OF THE MODIFIED FUNCTION */
 
/*          F(X+STP*S) - F(X) - FTOL*STP*(GRADF(X)'S). */
 
/*     IF A STEP IS OBTAINED FOR WHICH THE MODIFIED FUNCTION */
/*     HAS A NONPOSITIVE FUNCTION VALUE AND NONNEGATIVE DERIVATIVE, */
/*     THEN THE INTERVAL OF UNCERTAINTY IS CHOSEN SO THAT IT */
/*     CONTAINS A MINIMIZER OF F(X+STP*S). */
 
/*     THE ALGORITHM IS DESIGNED TO FIND A STEP WHICH SATISFIES */
/*     THE SUFFICIENT DECREASE CONDITION */
 
/*           F(X+STP*S) .LE. F(X) + FTOL*STP*(GRADF(X)'S), */
 
/*     AND THE CURVATURE CONDITION */
 
/*           ABS(GRADF(X+STP*S)'S)) .LE. GTOL*ABS(GRADF(X)'S). */
 
/*     IF FTOL IS LESS THAN GTOL AND IF, FOR EXAMPLE, THE FUNCTION */
/*     IS BOUNDED BELOW, THEN THERE IS ALWAYS A STEP WHICH SATISFIES */
/*     BOTH CONDITIONS. IF NO STEP CAN BE FOUND WHICH SATISFIES BOTH */
/*     CONDITIONS, THEN THE ALGORITHM USUALLY STOPS WHEN ROUNDING */
/*     ERRORS PREVENT FURTHER PROGRESS. IN THIS CASE STP ONLY */
/*     SATISFIES THE SUFFICIENT DECREASE CONDITION. */
 
/*     THE SUBROUTINE STATEMENT IS */
 
/*        SUBROUTINE MCSRCH(N,X,F,G,S,STP,FTOL,XTOL, MAXFEV,INFO,NFEV,WA) */
/*     WHERE */
 
/*       N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER */
/*         OF VARIABLES. */
 
/*       X IS AN ARRAY OF LENGTH N. ON INPUT IT MUST CONTAIN THE */
/*         BASE POINT FOR THE LINE SEARCH. ON OUTPUT IT CONTAINS */
/*         X + STP*S. */
 
/*       F IS A VARIABLE. ON INPUT IT MUST CONTAIN THE VALUE OF F */
/*         AT X. ON OUTPUT IT CONTAINS THE VALUE OF F AT X + STP*S. */
 
/*       G IS AN ARRAY OF LENGTH N. ON INPUT IT MUST CONTAIN THE */
/*         GRADIENT OF F AT X. ON OUTPUT IT CONTAINS THE GRADIENT */
/*         OF F AT X + STP*S. */
 
/*       S IS AN INPUT ARRAY OF LENGTH N WHICH SPECIFIES THE */
/*         SEARCH DIRECTION. */
 
/*       STP IS A NONNEGATIVE VARIABLE. ON INPUT STP CONTAINS AN */
/*         INITIAL ESTIMATE OF A SATISFACTORY STEP. ON OUTPUT */
/*         STP CONTAINS THE FINAL ESTIMATE. */
 
/*       FTOL AND GTOL ARE NONNEGATIVE INPUT VARIABLES. (In this reverse */
/*         communication implementation GTOL is defined in a COMMON */
/*         statement.) TERMINATION OCCURS WHEN THE SUFFICIENT DECREASE */
/*         CONDITION AND THE DIRECTIONAL DERIVATIVE CONDITION ARE */
/*         SATISFIED. */
 
/*       XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION OCCURS */
/*         WHEN THE RELATIVE WIDTH OF THE INTERVAL OF UNCERTAINTY */
/*         IS AT MOST XTOL. */
 
/*       STPMIN AND STPMAX ARE NONNEGATIVE INPUT VARIABLES WHICH */
/*         SPECIFY LOWER AND UPPER BOUNDS FOR THE STEP. (In this reverse */
/*         communication implementatin they are defined in a COMMON */
/*         statement). */
 
/*       MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION */
/*         OCCURS WHEN THE NUMBER OF CALLS TO FCN IS AT LEAST */
/*         MAXFEV BY THE END OF AN ITERATION. */
 
/*       INFO IS AN INTEGER OUTPUT VARIABLE SET AS FOLLOWS: */
 
/*         INFO = 0  IMPROPER INPUT PARAMETERS. */
 
/*        INFO =-1  A RETURN IS MADE TO COMPUTE THE FUNCTION AND GRADIENT.  */
/*       NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF */
/*         CALLS TO FCN. */
 
/*       WA IS A WORK ARRAY OF LENGTH N. */
 
/*     SUBPROGRAMS CALLED */
 
/*       MCSTEP */
 
/*       FORTRAN-SUPPLIED...ABS,MAX,MIN */
 
/*     ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. JUNE 1983 */
/*     JORGE J. MORE', DAVID J. THUENTE */
 
/*     ********** */
 
#endif // #ifndef itkMoreThuenteLineSearchOptimizer_h