The base class for all the independence tests used for learning. More...

#include <agrum/BN/learning/scores_and_tests/independenceTest.h>

Inheritance diagram for gum::learning::IndependenceTest:

Collaboration diagram for gum::learning::IndependenceTest:

Public Member Functions
Constructors / Destructors
	IndependenceTest (const DBRowGeneratorParser &parser, const Prior &external_prior, const std::vector< std::pair< std::size_t, std::size_t > > &ranges, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
	default constructor
	IndependenceTest (const DBRowGeneratorParser &parser, const Prior &external_prior, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
	default constructor
virtual IndependenceTest *	clone () const =0
	virtual copy constructor
virtual	~IndependenceTest ()
	destructor
Accessors / Modifiers
virtual void	setNumberOfThreads (Size nb)
	sets the number max of threads that can be used
virtual Size	getNumberOfThreads () const
	returns the current max number of threads of the scheduler
virtual bool	isGumNumberOfThreadsOverriden () const
	indicates whether the user set herself the number of threads
virtual void	setMinNbRowsPerThread (const std::size_t nb) const
	changes the number min of rows a thread should process in a multithreading context
virtual std::size_t	minNbRowsPerThread () const
	returns the minimum of rows that each thread should process
void	setRanges (const std::vector< std::pair< std::size_t, std::size_t > > &new_ranges)
	sets new ranges to perform the counts used by the independence test
void	clearRanges ()
	reset the ranges to the one range corresponding to the whole database
const std::vector< std::pair< std::size_t, std::size_t > > &	ranges () const
	returns the current ranges
double	score (const NodeId var1, const NodeId var2)
	returns the score of a pair of nodes
double	score (const NodeId var1, const NodeId var2, const std::vector< NodeId > &rhs_ids)
	returns the score of a pair of nodes given some other nodes
virtual void	clear ()
	clears all the data structures from memory, including the cache
virtual void	clearCache ()
	clears the current cache
virtual void	useCache (const bool on_off)
	turn on/off the use of a cache of the previously computed score
const Bijection< NodeId, std::size_t > &	nodeId2Columns () const
	return the mapping between the columns of the database and the node ids
const DatabaseTable &	database () const
	return the database used by the score

Protected Member Functions
	IndependenceTest (const IndependenceTest &from)
	copy constructor
	IndependenceTest (IndependenceTest &&from)
	move constructor
IndependenceTest &	operator= (const IndependenceTest &from)
	copy operator
IndependenceTest &	operator= (IndependenceTest &&from)
	move operator
virtual double	score_ (const IdCondSet &idset)=0
	returns the score for a given IdCondSet
std::vector< double >	marginalize_ (const std::size_t node_2_marginalize, const std::size_t X_size, const std::size_t Y_size, const std::size_t Z_size, const std::vector< double > &N_xyz) const
	returns a counting vector where variables are marginalized from N_xyz

Protected Attributes
const double	one_log2_ {M_LOG2E}
	1 / log(2)
Prior *	prior_ {nullptr}
	the expert knowledge a priorwe add to the contingency tables
RecordCounter	counter_
	the record counter used for the counts over discrete variables
ScoringCache	cache_
	the scoring cache
bool	use_cache_ {true}
	a Boolean indicating whether we wish to use the cache
const std::vector< NodeId >	empty_ids_
	an empty vector

Detailed Description

The base class for all the independence tests used for learning.

Definition at line 68 of file independenceTest.h.

Constructor & Destructor Documentation

◆ IndependenceTest() [1/4]

gum::learning::IndependenceTest::IndependenceTest	(	const DBRowGeneratorParser &	parser,
		const Prior &	external_prior,
		const std::vector< std::pair< std::size_t, std::size_t > > &	ranges,
		const Bijection< NodeId, std::size_t > &	nodeId2columns = Bijection< NodeId, std::size_t >() )

default constructor

Parameters

parser	the parser used to parse the database
external_prior	An prior that we add to the computation of the score (this should come from expert knowledge): this consists in adding numbers to counts in the contingency tables
ranges	a set of pairs {(X1,Y1),...,(Xn,Yn)} of database's rows indices. The counts are then performed only on the union of the rows [Xi,Yi), i in {1,...,n}. This is useful, e.g, when performing cross validation tasks, in which part of the database should be ignored. An empty set of ranges is equivalent to an interval [X,Y) ranging over the whole database.
nodeId2Columns	a mapping from the ids of the nodes in the graphical model to the corresponding column in the DatabaseTable parsed by the parser. This enables estimating from a database in which variable A corresponds to the 2nd column the parameters of a BN in which variable A has a NodeId of 5. An empty nodeId2Columns bijection means that the mapping is an identity, i.e., the value of a NodeId is equal to the index of the column in the DatabaseTable.

Warning: If nodeId2columns is not empty, then only the scores over the ids belonging to this bijection can be computed: applying method score() over other ids will raise exception NotFound.

References ranges().

Referenced by IndependenceTest(), IndependenceTest(), clone(), operator=(), and operator=().

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◆ IndependenceTest() [2/4]

gum::learning::IndependenceTest::IndependenceTest	(	const DBRowGeneratorParser &	parser,
		const Prior &	external_prior,
		const Bijection< NodeId, std::size_t > &	nodeId2columns = Bijection< NodeId, std::size_t >() )

default constructor

Parameters

parser	the parser used to parse the database
external_prior	An prior that we add to the computation of the score (this should come from expert knowledge): this consists in adding numbers to counts in the contingency tables
nodeId2Columns	a mapping from the ids of the nodes in the graphical model to the corresponding column in the DatabaseTable parsed by the parser. This enables estimating from a database in which variable A corresponds to the 2nd column the parameters of a BN in which variable A has a NodeId of 5. An empty nodeId2Columns bijection means that the mapping is an identity, i.e., the value of a NodeId is equal to the index of the column in the DatabaseTable.

Warning: If nodeId2columns is not empty, then only the scores over the ids belonging to this bijection can be computed: applying method score() over other ids will raise exception NotFound.

◆ ~IndependenceTest()

virtual gum::learning::IndependenceTest::~IndependenceTest ( )

virtual

destructor

◆ IndependenceTest() [3/4]

gum::learning::IndependenceTest::IndependenceTest ( const IndependenceTest & from )

protected

copy constructor

References IndependenceTest().

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◆ IndependenceTest() [4/4]

gum::learning::IndependenceTest::IndependenceTest ( IndependenceTest && from )

protected

move constructor

References IndependenceTest().

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Member Function Documentation

◆ clear()

virtual void gum::learning::IndependenceTest::clear ( )

virtual

clears all the data structures from memory, including the cache

Reimplemented in gum::learning::KNML.

◆ clearCache()

virtual void gum::learning::IndependenceTest::clearCache ( )

virtual

clears the current cache

Reimplemented in gum::learning::KNML.

◆ clearRanges()

void gum::learning::IndependenceTest::clearRanges ( )

reset the ranges to the one range corresponding to the whole database

Referenced by gum::learning::KNML::operator=().

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◆ clone()

virtual IndependenceTest * gum::learning::IndependenceTest::clone ( ) const

pure virtual

virtual copy constructor

Implemented in gum::learning::IndepTestChi2, gum::learning::IndepTestG2, and gum::learning::KNML.

References IndependenceTest().

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◆ database()

const DatabaseTable & gum::learning::IndependenceTest::database ( ) const

return the database used by the score

Referenced by gum::learning::KNML::useCache().

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◆ getNumberOfThreads()

virtual Size gum::learning::IndependenceTest::getNumberOfThreads ( ) const

virtual

returns the current max number of threads of the scheduler

Implements gum::IThreadNumberManager.

Reimplemented in gum::learning::KNML.

Referenced by gum::learning::KNML::operator=().

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◆ isGumNumberOfThreadsOverriden()

virtual bool gum::learning::IndependenceTest::isGumNumberOfThreadsOverriden ( ) const

virtual

indicates whether the user set herself the number of threads

Implements gum::IThreadNumberManager.

Reimplemented in gum::learning::KNML.

Referenced by gum::learning::KNML::operator=().

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◆ marginalize_()

std::vector< double > gum::learning::IndependenceTest::marginalize_	(	const std::size_t	node_2_marginalize,
		const std::size_t	X_size,
		const std::size_t	Y_size,
		const std::size_t	Z_size,
		const std::vector< double > &	N_xyz ) const

protected

returns a counting vector where variables are marginalized from N_xyz

Parameters

node_2_marginalize	indicates which node(s) shall be marginalized: 0 means that X should be marginalized 1 means that Y should be marginalized 2 means that Z should be marginalized
X_size	the domain size of variable X
Y_size	the domain size of variable Y
Z_size	the domain size of the set of conditioning variables Z
N_xyz	a counting vector of dimension X * Y * Z (in this order)

◆ minNbRowsPerThread()

virtual std::size_t gum::learning::IndependenceTest::minNbRowsPerThread ( ) const

virtual

returns the minimum of rows that each thread should process

Reimplemented in gum::learning::KNML.

Referenced by gum::learning::KNML::operator=().

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◆ nodeId2Columns()

const Bijection< NodeId, std::size_t > & gum::learning::IndependenceTest::nodeId2Columns ( ) const

return the mapping between the columns of the database and the node ids

Warning: An empty nodeId2Columns bijection means that the mapping is an identity, i.e., the value of a NodeId is equal to the index of the column in the DatabaseTable.

Referenced by gum::learning::KNML::useCache().

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◆ operator=() [1/2]

IndependenceTest & gum::learning::IndependenceTest::operator= ( const IndependenceTest & from )

protected

copy operator

References IndependenceTest().

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◆ operator=() [2/2]

IndependenceTest & gum::learning::IndependenceTest::operator= ( IndependenceTest && from )

protected

move operator

References IndependenceTest().

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◆ ranges()

const std::vector< std::pair< std::size_t, std::size_t > > & gum::learning::IndependenceTest::ranges ( ) const

returns the current ranges

Referenced by IndependenceTest(), gum::learning::IndepTestChi2::IndepTestChi2(), gum::learning::IndepTestG2::IndepTestG2(), and gum::learning::KNML::operator=().

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◆ score() [1/2]

double gum::learning::IndependenceTest::score	(	const NodeId	var1,
		const NodeId	var2 )

returns the score of a pair of nodes

Referenced by gum::learning::KNML::operator=().

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◆ score() [2/2]

double gum::learning::IndependenceTest::score	(	const NodeId	var1,
		const NodeId	var2,
		const std::vector< NodeId > &	rhs_ids )

returns the score of a pair of nodes given some other nodes

Parameters

var1	the first variable on the left side of the conditioning bar
var2	the second variable on the left side of the conditioning bar
rhs_ids	the set of variables on the right side of the conditioning bar

◆ score_()

virtual double gum::learning::IndependenceTest::score_ ( const IdCondSet & idset )

protectedpure virtual

returns the score for a given IdCondSet

Exceptions

OperationNotAllowed is raised if the score does not support calling method score such an idset (due to too many/too few variables in the left hand side or the right hand side of the idset).

Implemented in gum::learning::IndepTestChi2, gum::learning::IndepTestG2, and gum::learning::KNML.

◆ setMinNbRowsPerThread()

virtual void gum::learning::IndependenceTest::setMinNbRowsPerThread ( const std::size_t nb ) const

virtual

changes the number min of rows a thread should process in a multithreading context

When computing score, several threads are used by record counters to perform counts on the rows of the database, the MinNbRowsPerThread method indicates how many rows each thread should at least process. This is used to compute the number of threads actually run. This number is equal to the min between the max number of threads allowed and the number of records in the database divided by nb.

Reimplemented in gum::learning::KNML.

Referenced by gum::learning::KNML::operator=().

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◆ setNumberOfThreads()

virtual void gum::learning::IndependenceTest::setNumberOfThreads ( Size nb )

virtual

sets the number max of threads that can be used

Parameters

nb	the number max of threads to be used. If this number is set to 0, then it is defaulted to aGrUM's max number of threads

Implements gum::IThreadNumberManager.

Reimplemented in gum::learning::KNML.

Referenced by gum::learning::KNML::operator=().

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◆ setRanges()

void gum::learning::IndependenceTest::setRanges ( const std::vector< std::pair< std::size_t, std::size_t > > & new_ranges )

sets new ranges to perform the counts used by the independence test

Parameters

ranges a set of pairs {(X1,Y1),...,(Xn,Yn)} of database's rows indices. The counts are then performed only on the union of the rows [Xi,Yi), i in {1,...,n}. This is useful, e.g, when performing cross validation tasks, in which part of the database should be ignored. An empty set of ranges is equivalent to an interval [X,Y) ranging over the whole database.

Referenced by gum::learning::KNML::operator=().

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◆ useCache()

virtual void gum::learning::IndependenceTest::useCache ( const bool on_off )

virtual

turn on/off the use of a cache of the previously computed score

Reimplemented in gum::learning::KNML.

Member Data Documentation

◆ cache_

ScoringCache gum::learning::IndependenceTest::cache_

protected

the scoring cache

Definition at line 222 of file independenceTest.h.

◆ counter_

RecordCounter gum::learning::IndependenceTest::counter_

protected

the record counter used for the counts over discrete variables

Definition at line 219 of file independenceTest.h.

◆ empty_ids_

const std::vector< NodeId > gum::learning::IndependenceTest::empty_ids_

protected

an empty vector

Definition at line 228 of file independenceTest.h.

◆ one_log2_

const double gum::learning::IndependenceTest::one_log2_ {M_LOG2E}

protected

1 / log(2)

Definition at line 213 of file independenceTest.h.

213{M_LOG2E};

M_LOG2E

#define M_LOG2E

Definition math_utils.h:55

◆ prior_

Prior* gum::learning::IndependenceTest::prior_ {nullptr}

protected

the expert knowledge a priorwe add to the contingency tables

Definition at line 216 of file independenceTest.h.

216{nullptr};

◆ use_cache_

bool gum::learning::IndependenceTest::use_cache_ {true}

protected

a Boolean indicating whether we wish to use the cache

Definition at line 225 of file independenceTest.h.

225{true};

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

agrum/base/stattests/independenceTest.h

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ IndependenceTest() [1/4]

◆ IndependenceTest() [2/4]

◆ ~IndependenceTest()

◆ IndependenceTest() [3/4]

◆ IndependenceTest() [4/4]

Member Function Documentation

◆ clear()

◆ clearCache()

◆ clearRanges()

◆ clone()

◆ database()

◆ getNumberOfThreads()

◆ isGumNumberOfThreadsOverriden()

◆ marginalize_()

◆ minNbRowsPerThread()

◆ nodeId2Columns()

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ ranges()

◆ score() [1/2]

◆ score() [2/2]

◆ score_()

◆ setMinNbRowsPerThread()

◆ setNumberOfThreads()

◆ setRanges()

◆ useCache()

Member Data Documentation

◆ cache_

◆ counter_

◆ empty_ids_

◆ one_log2_

◆ prior_

◆ use_cache_