lineoptimizerparabola< LNPATH, T > Class Template Reference

Minimize fn on a 1D path in N dimensional space by fitting a parabola. More...

#include <lineoptimizerparabola.h>

Inheritance diagram for lineoptimizerparabola< LNPATH, T >:

Collaboration diagram for lineoptimizerparabola< LNPATH, T >:

List of all members.

Public Types
typedef lineoptimizergold2 < LNPATH, T >	lopg
Public Member Functions
	lineoptimizerparabola (LNPATH linepath_)
	Initialize memory, does no computations.
bool const	parabolamin (T &tnew, uintc a0, uintc a1, uintc a2) const
	From consecutive indexed points fit a parabola for tnew.
void	operator++ ()
	One iteration of the line minimization algorithm.
Static Public Attributes
static T	zero = 1E-20
	A small positive number used for zero tests.

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Detailed Description

template<typename LNPATH, typename T>
class lineoptimizerparabola< LNPATH, T >

Minimize fn on a 1D path in N dimensional space by fitting a parabola.

Usage

Example

  double d1[] = {0.0,1.0,1.0};
  double x0[] = {0.0,0.0,0.0};
  parab2 fn;
  typedef linepathd1<parab2&,double*,double*,double> lpth;
  lineoptimizerparabola<lpth,double> 
    opt( lpth(3,fn,fn.xi,x0,d1) );

  opt.reset(0.0,5.0);
  for (uint i=0; i<10; ++i)
  {
    ++opt;
    opt.printstate();
  }

Definition at line 42 of file lineoptimizerparabola.h.

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Member Typedef Documentation

template<typename LNPATH , typename T >

typedef lineoptimizergold2<LNPATH,T> lineoptimizerparabola< LNPATH, T >::lopg

Definition at line 46 of file lineoptimizerparabola.h.

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Constructor & Destructor Documentation

template<typename LNPATH , typename T >

lineoptimizerparabola< LNPATH, T >::lineoptimizerparabola

(

LNPATH

linepath_

)

[inline]

Initialize memory, does no computations.

Definition at line 52 of file lineoptimizerparabola.h.

                                           :
    lineoptimizergold2<LNPATH,T>(linepath_) {}

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Member Function Documentation

template<typename LNPATH , typename T >

void lineoptimizerparabola< LNPATH, T >::operator++

(

)

[inline]

One iteration of the line minimization algorithm.

Reimplemented from lineoptimizergold2< LNPATH, T >.

Definition at line 110 of file lineoptimizerparabola.h.

References lineoptimizergold2< LNPATH, T >::ai, lineoptimizergold2< LNPATH, T >::fti, lineoptimizergold2< LNPATH, T >::goldratio, lineoptimizergold2< LNPATH, T >::lengthgold, lineoptimizergold2< LNPATH, T >::linepath, lineoptimizerparabola< LNPATH, T >::parabolamin(), lineoptimizergold2< LNPATH, T >::printstate(), lineoptimizergold2< LNPATH, T >::resetInnerTwoPoints(), lineoptimizergold2< LNPATH, T >::ti, and lineoptimizergold2< LNPATH, T >::verify().

{
  lopg::lengthgold *= lopg::goldratio;
//cout << SHOW(lengthgold) << endl;

  // Minimization
  uint rej;

  T w;

  //printstate();

  // Test - reject x0 if successful.
  if (lopg::fti[lopg::ai[2]]<lopg::fti[lopg::ai[1]])
  {

    // If parabola minimization fails, do two gold section minimizations
    if (parabolamin(w,lopg::ai[1],lopg::ai[2],lopg::ai[3])==false)
    {
cout << "parabolamin failed in x0 rejection." << endl;

      rej = lopg::ai[0];
//cout << "parab min failed, rejecting x0" << endl;
lopg::printstate();
      lopg::ai[0] = lopg::ai[1];
      lopg::ai[1] = rej;
      lopg::resetInnerTwoPoints();

      return;
    }

//cout << "Reject x0" << endl;
    rej = lopg::ai[0];
    lopg::ti[rej] = w;
    lopg::linepath.fneval(lopg::fti[rej],lopg::ti[rej]);
    lopg::ai[0] = lopg::ai[1];

    if (w<lopg::ti[lopg::ai[2]])
      lopg::ai[1] = rej;
    else
    {
      lopg::ai[1] = lopg::ai[2];
      lopg::ai[2] = rej;
    }

    //convergencetest();

    //printstate();
    assert(lopg::verify());
    return;
  }


//cout << "Reject x3" << endl;
  rej = lopg::ai[3];

  // Test - reject x3 if successful.
  if (lopg::fti[lopg::ai[1]]<lopg::fti[lopg::ai[2]])
  {

    // If parabola minimization fails, do two gold section minimizations
    if (parabolamin(w,lopg::ai[0],lopg::ai[1],lopg::ai[2])==false)
    {
cout << "parabolamin failed in x3 rejection." << endl;
//cout << "parab min failed, rejecting x3" << endl;
      rej = lopg::ai[3];

      lopg::ai[3] = lopg::ai[2];
      lopg::ai[2] = rej;
      lopg::resetInnerTwoPoints();

      return;
    }

//cout << "Reject x0" << endl;
    rej = lopg::ai[3];
    lopg::ti[rej] = w;
    lopg::linepath.fneval(lopg::fti[rej],lopg::ti[rej]);
    lopg::ai[3] = lopg::ai[2];

    if (w<lopg::ti[lopg::ai[1]])
    {
      lopg::ai[2] = lopg::ai[1];
      lopg::ai[1] = rej;
    }
    else
    {
      lopg::ai[2] = rej;
    }

    //printstate();
    assert(lopg::verify());
    return;
  }

  // No interval can be rejected because both points are the same height.
  // This is a hack. If the value between 1 and 2 is the same then the method
  // will fail.  
  lopg::ti[lopg::ai[1]] += lopg::ti[ lopg::ai[2] ];
  lopg::ti[lopg::ai[1]] *= (T)0.5;
  lopg::linepath.fneval(lopg::fti[lopg::ai[1]],lopg::ti[lopg::ai[1]]);

}

template<typename LNPATH , typename T >

bool const lineoptimizerparabola< LNPATH, T >::parabolamin	(	T &	tnew,
		uintc	a0,
		uintc	a1,
		uintc	a2
	)			const [inline]

From consecutive indexed points fit a parabola for tnew.

Definition at line 217 of file lineoptimizerparabola.h.

Referenced by lineoptimizerparabola< LNPATH, T >::operator++().

{
// Scale and minimize
// max/min at -b/2a = (-q^2*f2+q^2*f0+f1-f0)/(2*(f1-f0+q(f0-f2))
// where q=(t1-t0)/(t2-t0)
  assert( lopg::ti[a2] != lopg::ti[a0] );

  T f5 = lopg::fti[a1]-lopg::fti[a0];
  T q = (lopg::ti[a1]-lopg::ti[a0])/(lopg::ti[a2]-lopg::ti[a0]);
  T den = (f5+q*(lopg::fti[a0]-lopg::fti[a2]))*2;
  if ( den*den < zero )
    return false;
  T num = q*q*(lopg::fti[a0]-lopg::fti[a2])+f5;
  T w = num/den;
  if (w<=(T)0.0)
    return false;
  if (w>=(T)1.0)
    return false;

  tnew = lopg::ti[a0] + (lopg::ti[a2]-lopg::ti[a0])*w;

  return true;
}

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Member Data Documentation

template<typename LNPATH , typename T >

T lineoptimizerparabola< LNPATH, T >::zero = 1E-20 [inline, static]

A small positive number used for zero tests.

Definition at line 49 of file lineoptimizerparabola.h.

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The documentation for this class was generated from the following file:

• patternsearch/lineoptimizerparabola.h