MoochoPack_MeritFunc_PenaltyParamUpdateWithMult_AddedStep.cpp

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#if 0

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#include <ostream>
#include <typeinfo>

#include "MoochoPack_MeritFunc_PenaltyParamUpdateWithMult_AddedStep.hpp"
#include "MoochoPack_NLPAlgoState.hpp"
#include "ConstrainedOptPack/src/VectorWithNorms.h"

namespace MoochoPack {

MeritFunc_PenaltyParamUpdateWithMult_AddedStep::MeritFunc_PenaltyParamUpdateWithMult_AddedStep(
      const merit_func_ptr_t& merit_func, value_type small_mu
    , value_type mult_factor, value_type kkt_near_sol )
  : MeritFunc_PenaltyParamUpdateGuts_AddedStep(merit_func,small_mu,mult_factor,kkt_near_sol)
{}

// Overridden from MeritFunc_PenaltyParamUpdateGuts_AddedStep

bool MeritFunc_PenaltyParamUpdateWithMult_AddedStep::min_mu(
  NLPAlgoState& s, value_type* min_mu ) const
{
  if ( s.lambda().updated_k(0) ) {
    *min_mu = s.lambda().get_k(0).norm_inf();
    return true;
  }
  return false;
}

void MeritFunc_PenaltyParamUpdateWithMult_AddedStep::print_min_mu_step(
  std::ostream& out, const std::string& L ) const
{
  out
    << L << "if lambda_k is updated then\n"
    << L << "    min_mu = norm( lambda_k, inf )\n"
    << L << "    update_mu = true\n"
    << L << "else\n"
    << L << "    update_mu = false\n"
    << L << "endif\n"
    ;
}

} // end namespace MoochoPack

#endif // 0