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NAME

       sc::EFCOpt -

       The EFCOpt class implements eigenvector following as described by Baker
       in J.

SYNOPSIS

       #include <efc.h>

       Inherits sc::Optimize.

   Public Member Functions
       EFCOpt (const Ref< KeyVal > &)
           The KeyVal constructor reads the following keywords:
       EFCOpt (StateIn &)
       void save_data_state (StateOut &)
           Save the base classes (with save_data_state) and the members in the
           same order that the StateIn CTOR initializes them.
       void apply_transform (const Ref< NonlinearTransform > &)
       void init ()
           Initialize the optimizer.
       int update ()
           Take a step.

   Protected Attributes
       int tstate
       int modef
       double maxabs_gradient
       double convergence_
       double accuracy_
       RefSymmSCMatrix hessian_
       Ref< HessianUpdate > update_
       RefSCVector last_mode_

Detailed Description

       The EFCOpt class implements eigenvector following as described by Baker
       in J.

       Comput. Chem., Vol 7, No 4, 385-395, 1986.

Constructor & Destructor Documentation

   sc::EFCOpt::EFCOpt (const Ref< KeyVal > &)
       The KeyVal constructor reads the following keywords: .IP "update" 1c
       This gives an HessianUpdate object. The default is to not update the
       hessian.

       transition_state
           If this is true than a transition state search will be performed.
           The default is false.

       mode_following
           If this is true, then the initial search direction for a transition
           state search will be choosen to similar to the first coordinate of
           the Function. The default is false.

       hessian
           By default, the guess hessian is obtained from the Function object.
           This keyword specifies an lower triangle array (the second index
           must be less than or equal to than the first) that replaces the
           guess hessian. If some of the elements are not given, elements from
           the guess hessian will be used.

       accuracy
           The accuracy with which the first gradient will be computed. If
           this is too large, it may be necessary to evaluate the first
           gradient point twice. If it is too small, it may take longer to
           evaluate the first point. The default is 0.0001.

Member Function Documentation

   void sc::EFCOpt::save_data_state (StateOut &) [virtual]
       Save the base classes (with save_data_state) and the members in the
       same order that the StateIn CTOR initializes them. This must be
       implemented by the derived class if the class has data.

       Reimplemented from sc::Optimize.

   int sc::EFCOpt::update () [virtual]
       Take a step. Returns 1 if the optimization has converged, otherwise 0.

       Implements sc::Optimize.

Author

       Generated automatically by Doxygen for MPQC from the source code.