QUESO::Algorithm< V, M > Class Template Reference

#include <Algorithm.h>

Public Member Functions
	Algorithm (const BaseEnvironment &env, const BaseTKGroup< V, M > &tk)
	~Algorithm ()
double	acceptance_ratio (MarkovChainPositionData< V > x, MarkovChainPositionData< V > y, const V &tk_pos_x, const V &tk_pos_y)
	Calculates the finite dimensional Metropolis-Hastings acceptance ratio. More...

Private Attributes
const BaseEnvironment &	m_env
const BaseTKGroup< V, M > &	m_tk

Detailed Description

template<class V = GslVector, class M = GslMatrix>
class QUESO::Algorithm< V, M >

Definition at line 35 of file Algorithm.h.

Constructor & Destructor Documentation

template<class V , class M >

QUESO::Algorithm< V, M >::Algorithm	(	const BaseEnvironment &	env,
		const BaseTKGroup< V, M > &	tk
	)

Definition at line 36 of file Algorithm.C.

  :
    m_env(env),
    m_tk(tk)
{
}

template<class V , class M >

QUESO::Algorithm< V, M >::~Algorithm

(

)

Definition at line 45 of file Algorithm.C.

{
}

Member Function Documentation

template<class V , class M >

double QUESO::Algorithm< V, M >::acceptance_ratio	(	MarkovChainPositionData< V >	x,
		MarkovChainPositionData< V >	y,
		const V &	tk_pos_x,
		const V &	tk_pos_y
	)

Calculates the finite dimensional Metropolis-Hastings acceptance ratio.

tk_pos_x is the position of the tk when evaluating for x tk_pos_y is the position of the tk when evaluating for y

This method is called by the delayed rejection procedure.

Definition at line 51 of file Algorithm.C.

References QUESO::MarkovChainPositionData< V >::logTarget(), QUESO::MarkovChainPositionData< V >::outOfTargetSupport(), QUESO::queso_isnan(), and QUESO::MarkovChainPositionData< V >::vecValues().

{
  double alphaQuotient = 0.;
  if ((x.outOfTargetSupport() == false) &&
      (y.outOfTargetSupport() == false)) {
    if ((x.logTarget() == -INFINITY) ||
        (x.logTarget() ==  INFINITY) ||
        ( queso_isnan(x.logTarget())      )) {
      std::cerr << "WARNING In Algorithm<V,M>::alpha(x,y)"
                << ", worldRank "       << m_env.worldRank()
                << ", fullRank "        << m_env.fullRank()
                << ", subEnvironment "  << m_env.subId()
                << ", subRank "         << m_env.subRank()
                << ", inter0Rank "      << m_env.inter0Rank()
                << ": x.logTarget() = " << x.logTarget()
                << ", x.values() = "    << x.vecValues()
                << ", y.values() = "    << y.vecValues()
                << std::endl;
    }
    else if ((y.logTarget() == -INFINITY           ) ||
             (y.logTarget() ==  INFINITY           ) ||
             ( queso_isnan(y.logTarget()) )) {
      std::cerr << "WARNING In Algorithm<V,M>::alpha(x,y)"
                << ", worldRank "       << m_env.worldRank()
                << ", fullRank "        << m_env.fullRank()
                << ", subEnvironment "  << m_env.subId()
                << ", subRank "         << m_env.subRank()
                << ", inter0Rank "      << m_env.inter0Rank()
                << ": y.logTarget() = " << y.logTarget()
                << ", x.values() = "    << x.vecValues()
                << ", y.values() = "    << y.vecValues()
                << std::endl;
    }
    else {
      double yLogTargetToUse = y.logTarget();

      if (m_tk.symmetric()) {
        alphaQuotient = std::exp(yLogTargetToUse - x.logTarget());

        if ((m_env.subDisplayFile()                   ) &&
            (m_env.displayVerbosity() >= 3            )) {
          *m_env.subDisplayFile() << "In Algorithm<V,M>::alpha(x,y)"
                                 << ": symmetric proposal case"
                                 << ", x = "               << x.vecValues()
                                 << ", y = "               << y.vecValues()
                                 << ", yLogTargetToUse = " << yLogTargetToUse
                                 << ", x.logTarget() = "   << x.logTarget()
                                 << ", alpha = "           << alphaQuotient
                                 << std::endl;
        }
      }
      else {
        double qyx = m_tk.rv(tk_pos_x).pdf().lnValue(x.vecValues());
        if ((m_env.subDisplayFile()                   ) &&
            (m_env.displayVerbosity() >= 10           )) {
          *m_env.subDisplayFile() << m_tk.rv(tk_pos_x).pdf() << std::endl;
        }
        double qxy = m_tk.rv(tk_pos_y).pdf().lnValue(y.vecValues());
        if ((m_env.subDisplayFile()                   ) &&
            (m_env.displayVerbosity() >= 10           )) {
          *m_env.subDisplayFile() << m_tk.rv(tk_pos_y).pdf() << std::endl;
        }
        alphaQuotient = std::exp(yLogTargetToUse +
                                 qyx -
                                 x.logTarget() -
                                 qxy);
        if ((m_env.subDisplayFile()                   ) &&
            (m_env.displayVerbosity() >= 3            )) {
          *m_env.subDisplayFile() << "In Algorithm<V,M>::alpha(x,y)"
                                 << ": asymmetric proposal case"
                                 << ", x = "               << x.vecValues()
                                 << ", y = "               << y.vecValues()
                                 << ", yLogTargetToUse = " << yLogTargetToUse
                                 << ", q(y,x) = "          << qyx
                                 << ", x.logTarget() = "   << x.logTarget()
                                 << ", q(x,y) = "          << qxy
                                 << ", alpha = "           << alphaQuotient
                                 << std::endl;
        }
      }
    } // protection logic against logTarget values
  }
  else {
    if ((m_env.subDisplayFile()                   ) &&
        (m_env.displayVerbosity() >= 10           )) {
      *m_env.subDisplayFile() << "In Algorithm<V,M>::alpha(x,y)"
                             << ": x.outOfTargetSupport = " << x.outOfTargetSupport()
                             << ", y.outOfTargetSupport = " << y.outOfTargetSupport()
                             << std::endl;
    }
  }

  return std::min(1.,alphaQuotient);
}

Member Data Documentation

template<class V = GslVector, class M = GslMatrix>

const BaseEnvironment& QUESO::Algorithm< V, M >::m_env

private

Definition at line 53 of file Algorithm.h.

template<class V = GslVector, class M = GslMatrix>

const BaseTKGroup<V, M>& QUESO::Algorithm< V, M >::m_tk

private

Definition at line 54 of file Algorithm.h.

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

• src/stats/inc/Algorithm.h
• src/stats/src/Algorithm.C