ConstrainedOptPack_vector_change_stats.cpp

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// Moocho: Multi-functional Object-Oriented arCHitecture for Optimization
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#include <limits>

#include "ConstrainedOptPack_vector_change_stats.hpp"
#include "DenseLinAlgPack_DVectorClass.hpp"
#include "DenseLinAlgPack_AssertOp.hpp"
#include "Teuchos_ScalarTraits.hpp"

void ConstrainedOptPack::vector_change_stats(
    const DVectorSlice& x, const DVectorSlice& d
  , value_type* max_term, size_type* max_k
  , value_type* min_term, size_type* min_k
  , value_type* av_term )
{
  typedef Teuchos::ScalarTraits<value_type> ST;
  DenseLinAlgPack::VopV_assert_sizes( x.dim(), d.dim() );
  const value_type
    min_num   = std::numeric_limits<value_type>::min(),
    inf     = std::numeric_limits<value_type>::max();
  // Initialize statistics
  *max_term = 0.0;
  *max_k    = 0;
  *min_term = inf;
  *min_k    = 0;
  *av_term  = 0.0;
  // Compute statistics
  DVectorSlice::const_iterator
    x_itr = x.begin(),
    d_itr = d.begin();
  for( size_type i = 1; x_itr != x.end(); ++i, ++d_itr, ++x_itr ) {
    // Compute this ratio and make sure we are not dividing by zero.
    // We only care about ratios less than 1.0 and also deal
    // with the case that both x(i) and d(i) are zero (in which
    // case the ratio should be zero since x(i) == x(i) + d(i)).
    const value_type
      term = ST::magnitude(*d_itr) / ( 1 + ST::magnitude(*x_itr) );
    if( term > *max_term ) {
      *max_term = term;
      *max_k    = i;
    }
    if( term < *min_term ) {
      *min_term = term;
      *min_k    = i;
    }
    *av_term += term;
  }
  *av_term = *av_term / x.dim();
}