<agrum/ID/inference/decisionTensor.h> More...

#include <decisionTensor.h>

Public Member Functions
	DecisionTensor ()
	~DecisionTensor ()
	DecisionTensor (const Tensor< GUM_SCALAR > &prob, const Tensor< GUM_SCALAR > &util)
	DecisionTensor (const DecisionTensor< GUM_SCALAR > &dp)
void	clear ()
DecisionTensor< GUM_SCALAR > &	operator= (const DecisionTensor< GUM_SCALAR > &src)
	DecisionTensor (DecisionTensor< GUM_SCALAR > &&dp)
DecisionTensor< GUM_SCALAR > &	operator= (DecisionTensor< GUM_SCALAR > &&src)
bool	operator== (const DecisionTensor< GUM_SCALAR > &p) const
const DiscreteVariable *	variable (std::string_view name) const
void	insertProba (const gum::Tensor< GUM_SCALAR > &proba)
void	insertUtility (const gum::Tensor< GUM_SCALAR > &util)
DecisionTensor< GUM_SCALAR >	operator* (const DecisionTensor< GUM_SCALAR > &dp1) const
DecisionTensor< GUM_SCALAR >	operator*= (const DecisionTensor< GUM_SCALAR > &dp1)
DecisionTensor< GUM_SCALAR >	operator^ (const gum::VariableSet &onto) const
DecisionTensor< GUM_SCALAR >	operator^ (const std::vector< std::string > &ontonames) const
std::pair< GUM_SCALAR, GUM_SCALAR >	meanVar ()
virtual std::string	toString () const

Static Public Member Functions
static Tensor< GUM_SCALAR >	divideEvenZero (const Tensor< GUM_SCALAR > &p1, const Tensor< GUM_SCALAR > &p2)
static DecisionTensor< GUM_SCALAR >	combination (const DecisionTensor< GUM_SCALAR > &dp1, const DecisionTensor< GUM_SCALAR > &dp2)
static DecisionTensor< GUM_SCALAR >	marginalization (const DecisionTensor< GUM_SCALAR > &dp, const gum::VariableSet &onto)
static DecisionTensor< GUM_SCALAR >	marginalization (const DecisionTensor< GUM_SCALAR > &dp, const std::vector< std::string > &ontonames)

Public Attributes
Tensor< GUM_SCALAR >	probPot
Tensor< GUM_SCALAR >	utilPot

Detailed Description

template<GUM_Numeric GUM_SCALAR>
class gum::DecisionTensor< GUM_SCALAR >

Tensor for optimization in LIMIDS (such as Single Policy Update)

Definition at line 63 of file decisionTensor.h.

Constructor & Destructor Documentation

◆ DecisionTensor() [1/4]

template<GUM_Numeric GUM_SCALAR>

gum::DecisionTensor< GUM_SCALAR >::DecisionTensor ( )

explicit

Definition at line 48 of file decisionTensor_tpl.h.

                                               {
    GUM_CONSTRUCTOR(DecisionTensor);
    probPot.fillWith(GUM_SCALAR(1));
    utilPot.fillWith(GUM_SCALAR(0));
  }

References DecisionTensor(), probPot, and utilPot.

Referenced by DecisionTensor(), DecisionTensor(), DecisionTensor(), DecisionTensor(), ~DecisionTensor(), combination(), marginalization(), marginalization(), operator*(), operator*=(), operator=(), operator=(), and operator==().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ ~DecisionTensor()

template<GUM_Numeric GUM_SCALAR>

gum::DecisionTensor< GUM_SCALAR >::~DecisionTensor ( )

Definition at line 55 of file decisionTensor_tpl.h.

                                                {
    GUM_DESTRUCTOR(DecisionTensor);
  }

References DecisionTensor().

Here is the call graph for this function:

◆ DecisionTensor() [2/4]

template<GUM_Numeric GUM_SCALAR>

gum::DecisionTensor< GUM_SCALAR >::DecisionTensor	(	const Tensor< GUM_SCALAR > &	prob,
		const Tensor< GUM_SCALAR > &	util )

Definition at line 60 of file decisionTensor_tpl.h.

                                                                                 :
      probPot(prob), utilPot(util) {
    GUM_CONSTRUCTOR(DecisionTensor);
  }

References DecisionTensor(), probPot, and utilPot.

Here is the call graph for this function:

◆ DecisionTensor() [3/4]

template<GUM_Numeric GUM_SCALAR>

gum::DecisionTensor< GUM_SCALAR >::DecisionTensor ( const DecisionTensor< GUM_SCALAR > & dp )

Definition at line 67 of file decisionTensor_tpl.h.

                                                                                     :
      probPot(dp.probPot), utilPot(dp.utilPot) {
    GUM_CONS_CPY(DecisionTensor);
  }

References DecisionTensor(), probPot, and utilPot.

Here is the call graph for this function:

◆ DecisionTensor() [4/4]

template<GUM_Numeric GUM_SCALAR>

gum::DecisionTensor< GUM_SCALAR >::DecisionTensor ( DecisionTensor< GUM_SCALAR > && dp )

Definition at line 73 of file decisionTensor_tpl.h.

                                                                                :
      probPot(std::forward< Tensor< GUM_SCALAR > >(dp.probPot)),
      utilPot(std::forward< Tensor< GUM_SCALAR > >(dp.utilPot)) {
    GUM_CONS_MOV(DecisionTensor);
  }

References DecisionTensor(), probPot, and utilPot.

Here is the call graph for this function:

Member Function Documentation

◆ clear()

template<GUM_Numeric GUM_SCALAR>

void gum::DecisionTensor< GUM_SCALAR >::clear ( )

Definition at line 80 of file decisionTensor_tpl.h.

                                           {
    gum::Tensor< GUM_SCALAR > p;
    p.fillWith(GUM_SCALAR(1));
    probPot = p;
    p.fillWith(GUM_SCALAR(0));
    utilPot = p;
  }

References gum::Tensor< GUM_SCALAR >::fillWith(), probPot, and utilPot.

Here is the call graph for this function:

◆ combination()

template<GUM_Numeric GUM_SCALAR>

DecisionTensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::combination	(	const DecisionTensor< GUM_SCALAR > &	dp1,
		const DecisionTensor< GUM_SCALAR > &	dp2 )

static

Definition at line 176 of file decisionTensor_tpl.h.

                                                                                         {
    return DecisionTensor< GUM_SCALAR >(dp1.probPot * dp2.probPot, dp1.utilPot + dp2.utilPot);
  }

References DecisionTensor(), probPot, and utilPot.

Referenced by operator*(), and operator*=().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ divideEvenZero()

template<GUM_Numeric GUM_SCALAR>

Tensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::divideEvenZero	(	const Tensor< GUM_SCALAR > &	p1,
		const Tensor< GUM_SCALAR > &	p2 )

static

Definition at line 164 of file decisionTensor_tpl.h.

                                                                                   {
    Tensor< GUM_SCALAR > res(p1);
    Instantiation        I(res);
    for (I.setFirst(); !I.end(); I.inc()) {
      if (p2[I] != 0) res.set(I, res[I] / p2[I]);
    }
    return res;
  }

References gum::Instantiation::end(), gum::Instantiation::inc(), and gum::Instantiation::setFirst().

Referenced by marginalization().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ insertProba()

template<GUM_Numeric GUM_SCALAR>

void gum::DecisionTensor< GUM_SCALAR >::insertProba ( const gum::Tensor< GUM_SCALAR > & proba )

Definition at line 128 of file decisionTensor_tpl.h.

                                                                                     {
    probPot *= proba;
  }

References probPot.

◆ insertUtility()

template<GUM_Numeric GUM_SCALAR>

void gum::DecisionTensor< GUM_SCALAR >::insertUtility ( const gum::Tensor< GUM_SCALAR > & util )

Definition at line 133 of file decisionTensor_tpl.h.

                                                                                      {
    utilPot += util;
  }

References utilPot.

◆ marginalization() [1/2]

template<GUM_Numeric GUM_SCALAR>

DecisionTensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::marginalization	(	const DecisionTensor< GUM_SCALAR > &	dp,
		const gum::VariableSet &	onto )

static

Definition at line 183 of file decisionTensor_tpl.h.

                                                                                            {
    const auto pr = dp.probPot.sumIn(onto);
    return DecisionTensor(pr, divideEvenZero((dp.probPot * dp.utilPot).sumIn(onto), pr));
  }

References DecisionTensor(), divideEvenZero(), probPot, and utilPot.

Referenced by marginalization(), operator^(), and operator^().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ marginalization() [2/2]

template<GUM_Numeric GUM_SCALAR>

DecisionTensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::marginalization	(	const DecisionTensor< GUM_SCALAR > &	dp,
		const std::vector< std::string > &	ontonames )

static

Definition at line 191 of file decisionTensor_tpl.h.

                                                                                               {
    gum::VariableSet onto;
    for (const auto& varname: ontonames) {
      onto.insert(dp.variable(varname));
    }
    return marginalization(dp, onto);
  }

References DecisionTensor(), gum::Set< Key >::insert(), marginalization(), and variable().

Here is the call graph for this function:

◆ meanVar()

template<GUM_Numeric GUM_SCALAR>

std::pair< GUM_SCALAR, GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::meanVar ( )

Definition at line 201 of file decisionTensor_tpl.h.

                                                                          {
    const auto       tmp = probPot * utilPot;
    const GUM_SCALAR s   = probPot.sum();
    const double     m   = tmp.sum() / s;
    const double     m2  = (tmp * utilPot).sum() / s;
    double           var = m2 - m * m;
    if (var < 0.0) var = 0.0;   // var is a small number<0 due to computation errors
    return std::pair< GUM_SCALAR, GUM_SCALAR >(m, var);
  }

References probPot, and utilPot.

◆ operator*()

template<GUM_Numeric GUM_SCALAR>

DecisionTensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::operator* ( const DecisionTensor< GUM_SCALAR > & dp1 ) const

Definition at line 139 of file decisionTensor_tpl.h.

                                                                                           {
    return DecisionTensor< GUM_SCALAR >::combination(*this, dp1);
  }

References DecisionTensor(), and combination().

Here is the call graph for this function:

◆ operator*=()

template<GUM_Numeric GUM_SCALAR>

DecisionTensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::operator*= ( const DecisionTensor< GUM_SCALAR > & dp1 )

Definition at line 145 of file decisionTensor_tpl.h.

                                                                                    {
    *this = DecisionTensor< GUM_SCALAR >::combination(*this, dp1);
    return *this;
  }

References DecisionTensor(), and combination().

Here is the call graph for this function:

◆ operator=() [1/2]

template<GUM_Numeric GUM_SCALAR>

DecisionTensor< GUM_SCALAR > & gum::DecisionTensor< GUM_SCALAR >::operator= ( const DecisionTensor< GUM_SCALAR > & src )

Definition at line 90 of file decisionTensor_tpl.h.

                                                                                   {
    GUM_OP_CPY(DecisionTensor);
    if (&src == this) return *this;
    probPot = src.probPot;
    utilPot = src.utilPot;
    return *this;
  }

References DecisionTensor(), probPot, and utilPot.

Here is the call graph for this function:

◆ operator=() [2/2]

template<GUM_Numeric GUM_SCALAR>

DecisionTensor< GUM_SCALAR > & gum::DecisionTensor< GUM_SCALAR >::operator= ( DecisionTensor< GUM_SCALAR > && src )

Definition at line 100 of file decisionTensor_tpl.h.

                                                                              {
    GUM_OP_MOV(DecisionTensor);
    if (&src == this) return *this;
    probPot = std::forward< Tensor< GUM_SCALAR > >(src.probPot);
    utilPot = std::forward< Tensor< GUM_SCALAR > >(src.utilPot);
    return *this;
  }

References DecisionTensor(), probPot, and utilPot.

Here is the call graph for this function:

◆ operator==()

template<GUM_Numeric GUM_SCALAR>

bool gum::DecisionTensor< GUM_SCALAR >::operator== ( const DecisionTensor< GUM_SCALAR > & p ) const

Definition at line 109 of file decisionTensor_tpl.h.

                                                                                         {
    // @see Evaluating Influence Diagrams using LIMIDS (2000) - section 3.3
    return ((p.probPot == this->probPot)
            && (p.probPot * p.utilPot == this->probPot * this->utilPot));
  }

References DecisionTensor(), probPot, and utilPot.

Here is the call graph for this function:

◆ operator^() [1/2]

template<GUM_Numeric GUM_SCALAR>

DecisionTensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::operator^ ( const gum::VariableSet & onto ) const

Definition at line 152 of file decisionTensor_tpl.h.

                                                                              {
    return DecisionTensor< GUM_SCALAR >::marginalization(*this, onto);
  }

References marginalization().

Here is the call graph for this function:

◆ operator^() [2/2]

template<GUM_Numeric GUM_SCALAR>

DecisionTensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::operator^ ( const std::vector< std::string > & ontonames ) const

Definition at line 158 of file decisionTensor_tpl.h.

                                                                                           {
    return DecisionTensor< GUM_SCALAR >::marginalization(*this, ontonames);
  }

References marginalization().

Here is the call graph for this function:

◆ toString()

template<GUM_Numeric GUM_SCALAR>

std::string gum::DecisionTensor< GUM_SCALAR >::toString ( ) const

virtual

Definition at line 212 of file decisionTensor_tpl.h.

                                                         {
    return "prob : " + probPot.toString() + "    util:" + utilPot.toString();
  }

References probPot, and utilPot.

Referenced by gum::operator<<().

Here is the caller graph for this function:

◆ variable()

template<GUM_Numeric GUM_SCALAR>

const DiscreteVariable * gum::DecisionTensor< GUM_SCALAR >::variable ( std::string_view name ) const

Definition at line 116 of file decisionTensor_tpl.h.

                                                                                          {
    for (const auto& v: probPot.variablesSequence()) {
      if (v->name() == name) return v;
    }
    for (const auto& v: utilPot.variablesSequence()) {
      if (v->name() == name) return v;
    }
 
    GUM_ERROR(NotFound, "'" << name << "' can not be found in DecisionTensor.")
  }

References GUM_ERROR, probPot, and utilPot.

Referenced by marginalization().

Here is the caller graph for this function:

Member Data Documentation

◆ probPot

template<GUM_Numeric GUM_SCALAR>

Tensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::probPot

Definition at line 65 of file decisionTensor.h.

Referenced by DecisionTensor(), DecisionTensor(), DecisionTensor(), DecisionTensor(), clear(), combination(), insertProba(), marginalization(), meanVar(), operator=(), operator=(), operator==(), toString(), and variable().

◆ utilPot

template<GUM_Numeric GUM_SCALAR>

Tensor< GUM_SCALAR > gum::DecisionTensor< GUM_SCALAR >::utilPot

Definition at line 66 of file decisionTensor.h.

Referenced by DecisionTensor(), DecisionTensor(), DecisionTensor(), DecisionTensor(), clear(), combination(), insertUtility(), marginalization(), meanVar(), operator=(), operator=(), operator==(), toString(), and variable().

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

agrum/ID/inference/tools/decisionTensor.h
agrum/ID/inference/tools/decisionTensor_tpl.h

Public Member Functions

Static Public Member Functions

Public Attributes

Detailed Description

Constructor & Destructor Documentation

◆ DecisionTensor() [1/4]

◆ ~DecisionTensor()

◆ DecisionTensor() [2/4]

◆ DecisionTensor() [3/4]

◆ DecisionTensor() [4/4]

Member Function Documentation

◆ clear()

◆ combination()

◆ divideEvenZero()

◆ insertProba()

◆ insertUtility()

◆ marginalization() [1/2]

◆ marginalization() [2/2]

◆ meanVar()

◆ operator*()

◆ operator*=()

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ operator==()

◆ operator^() [1/2]

◆ operator^() [2/2]

◆ toString()

◆ variable()

Member Data Documentation

◆ probPot

◆ utilPot