Provides the core functionality for the Bayesian network learning problem. More...

#include <string.h>
#include <ctype.h>
#include <float.h>
#include "probdata_bn.h"
#include "pedigrees.h"
#include "pedigree_scorer.h"
#include "cons_dagcluster.h"
#include "cons_ci.h"
#include "cons_chordal.h"
#include "cons_distinguishedrep.h"
#include "heur_sinks.h"
#include "utils.h"
#include "output.h"
#include "metadata.h"
#include "scoring.h"
#include "scip/misc.h"
#include "disp_clearcols.h"
#include "event_splitdag.h"
#include "cons_lop.h"
#include "cons_partialordering.h"
#include "cons_vanilla.h"

Include dependency graph for probdata_bn.c:

Macros
#define	DEFAULT_GOBNILP_INPUT_FORMAT "jkl"

Functions
static SCIP_RETCODE	addAcyclicityConstraints (SCIP scip, ParentSetData psd)
	Adds the acyclity constraints to the problem. More...

static SCIP_RETCODE	addAdditionalConstraints (SCIP scip, ParentSetData psd)
	Adds constraints ruling out immoralities in the DAG. More...

static SCIP_RETCODE	addAncestorVariables (SCIP scip, ParentSetData psd)
	If gobnilp/ancestorvars == TRUE, creates binary variables encoding the ancestor relation Creates binary variables anc[i][j] where anc[i][j]==1 iff j is an ancestor of i If gobnilp/useconspartialordering == TRUE, the partial order constraint is used on these variables. More...

static SCIP_RETCODE	addArrowVariables (SCIP scip, ParentSetData psd)
	Adds variables representing directed and undirected edges The branching priority for these variables is set at 10, so typically SCIP will branch on these variables rather than parent set variables. More...

static SCIP_RETCODE	addEdgeNumberConstraints (SCIP scip, ParentSetData psd)
	Adds constraints on the number of edges in the DAG. More...

static SCIP_RETCODE	addFounderConstraints (SCIP scip, ParentSetData psd)
	Adds constraints on the number of possible founders. More...

static SCIP_RETCODE	addGeneralDAGConstraints (SCIP scip, ParentSetData psd)
	Adds general structural constraints to the DAG. More...

static SCIP_RETCODE	addImsetVariables (SCIP scip, ParentSetData psd)
	The imsetvar for a subset of nodes = 1 iff one of the elements in the subset has all the others as parents. More...

static SCIP_RETCODE	addKBestMECVariables (SCIP scip, ParentSetData psd)

static SCIP_RETCODE	addNChildrenVars (SCIP scip, const ParentSetData psd)
	Adds variables which count how many children a node has.

static SCIP_RETCODE	addOneParentSetConstraints (SCIP scip, ParentSetData psd)
	Adds the constraints that there must be one parent set to the problem. More...

static SCIP_RETCODE	addOrderedCoveredArcConstraints (SCIP scip, ParentSetData psd)
	Adds constraints ruling out covered arcs from lower to higher vertices. More...

static SCIP_RETCODE	addParentNumberConstraints (SCIP scip, const ParentSetData psd)
	Adds constraints on the number of nodes that can be parents. More...

static SCIP_RETCODE	addParentVariables (SCIP scip, ParentSetData psd, SCIP_Real **scores)
	Creates and adds the parent variables to the problem. More...

static SCIP_RETCODE	addPaSizeVariables (SCIP scip, ParentSetData psd)
	If gobnilp/pasizevars == TRUE adds and sets the branching priorities of variables representing parent set size. More...

static SCIP_RETCODE	addPosindVariables (SCIP scip, ParentSetData psd)
	If gobnilp/posindvars == TRUE, adds binary variables indicating the position of nodes in a total order consistent with a DAG solution. More...

static SCIP_RETCODE	addPosVariables (SCIP scip, ParentSetData psd)
	If gobnilp/posvars == TRUE, creates integer variables giving a generation number for each node If a node is a founder its generation number is 0 If j is a parent of i its generation number is strictly less than i's An upper bound on any such variable can be set using gobnilp/maxpos Uses an Indicator constraint. More...

static SCIP_RETCODE	addTotalorderVariables (SCIP scip, ParentSetData psd)
	If gobnilp/totalordervars == TRUE, creates, and sets the branching priority for, binary variables encoding a total order consistent with a DAG solution Creates binary variables order[i][j] where order[i][j]==1 if i comes after j in the total ordering. More...

static SCIP_RETCODE	ancestor_constraint (SCIP scip, ParentSetData psd, int i, int j, SCIP_Bool truthvalue)
	Adds a constraint stating that an ancestor relation must be present or absent. More...

static SCIP_RETCODE	BN_addMECNonRepetitionConstraint (SCIP *scip, int run)
	Adds a constraint that prevents networks in the same MEC as the current best network being found again. More...

SCIP_RETCODE	BN_addNonRepetitionConstraint (SCIP *scip, int run)
	Adds a constraint that prevents the current best network being found again. More...

SCIP_RETCODE	BN_addParameters (SCIP *scip)
	Adds GOBNILP specific parameters to those recognised by SCIP. More...

SCIP_RETCODE	BN_doIterativePrint (SCIP scip, MA_info ma_info, int run)
	Prints appropriate information about each optimal solution obtained. More...

int	BN_getNumberOfRepeats (SCIP *scip)
	Gets the number of most likely Bayesian networks that should be found. More...

SCIP_RETCODE	BN_includePlugins (SCIP *scip)
	Includes all plugins needed by the problem. More...

SCIP_RETCODE	BN_printcountsols (SCIP scip, char filename)
	Prints solutions found using countsols. More...

SCIP_RETCODE	BN_printHeader (SCIP *scip)
	Prints a header which describes the GOBNILP and SCIP systems being used. More...

SCIP_RETCODE	BN_printParameters (SCIP *scip)
	Prints any of the current SCIP or GOBNILP parameters not at their default value. More...

SCIP_RETCODE	BN_printProblem (SCIP *scip, int run)
	Prints the current problem. More...

SCIP_RETCODE	BN_printScores (SCIP *scip)
	Prints the scores for the family variables in Jaakkola format. More...

SCIP_RETCODE	BN_readProblem (SCIP scip, char inputformat, char frequencyfile, const char filename)
	Reads in a problem from a file. More...

SCIP_RETCODE	BN_setParamaterDefaults (SCIP *scip)
	Sets various built-in SCIP parameters to suitable GOBNILP values. More...

SCIP_RETCODE	BN_suppresscols (SCIP *scip)
	Suppresses output columns according to the value of parameter gobnilp/verblevelsetcols. More...

static SCIP_RETCODE	ci_constraint (SCIP scip, ParentSetData psd, const char a_str, const char b_str, const char *s_str)
	Adds a conditional independence (ci) constraint. More...

static int	countParentSets (FILE *file)

static int	countVars (FILE *file)

static SCIP_RETCODE	createBasicModel (SCIP scip, ParentSetData psd, SCIP_Real **scores)
	Adds the variables and constraints needed for the basic DAG learning problem. More...

static SCIP_Bool	differ (SCIP scip, ParentSetData psd, int i, int ki1, int ki2, int j)
	Determines if two parent sets differ by just a single given item. More...

static SCIP_RETCODE	edge_constraint (SCIP scip, ParentSetData psd, int i, int j, SCIP_Bool undirected, SCIP_Bool truthvalue)
	Adds a constraint stating that an edge must be present or absent. More...

static void	extractMetaNameAndValue (const char string, char name, char *value)

static SCIP_RETCODE	getDelimiters (SCIP scip, int num_delims, char *delims, SCIP_Bool merge_delims)
	Gets the delimiter information needed to read in information from files. More...

static char *	getInputFormat (SCIP scip, char inputformat, const char *filename)
	Gets the format in which the input file has been given. More...

static SCIP_RETCODE	getProblemName (const char filename, char probname, int maxSize)
	Gets a problem name based on the file from which it was read. More...

static SCIP_RETCODE	immorality_constraint (SCIP scip, ParentSetData psd, int i, int j, int child, SCIP_Bool truthvalue)
	Adds a constraint enforcing or preventing an immorality constraint. More...

static SCIP_RETCODE	order_constraint (SCIP scip, ParentSetData psd, int i, int j)
	Adds a constraint stating that variable i must come before variable j in any variable ordering consistent with the learned network This works by simply fixing the relevant total order variable An error is generated if the user has not asked for the total order constraint handler to be used. More...

static SCIP_RETCODE	parseSet (SCIP scip, ParentSetData psd, const char str, int set, int n_set, SCIP_Bool success)
	Parses a string to extract a set from it. More...

static SCIP_RETCODE	process_constraint (SCIP scip, ParentSetData psd, const char *line)
	Adds a constraint on the DAG structure. More...

static SCIP_RETCODE	readProblemInCIPFormat (SCIP scip, const char filename)
	Reads a problem from a file in cip format. More...

static SCIP_RETCODE	readProblemInJaakkolaFormat (SCIP scip, const char filename, ParentSetData psd, SCIP_Real *scores, PropertyData prop)
	Reads local score BN file (in Jaakkola format) More...

static SCIP_RETCODE	readProblemInNonCIPFormat (SCIP scip, char frequencyfile, const char filename, char format)
	Reads a problem from a file in a format other than CIP. More...

static SCIP_RETCODE	readProblemInPSSFormat (SCIP scip, const char filename, ParentSetData psd, SCIP_Real *scores, PropertyData prop)
	Reads local score BN file (in PSS format) More...

static	SCIP_DECL_PROBDELORIG (probdelorigBN)
	delete problem data

static SCIP_RETCODE	setBranchingPriorities (SCIP scip, ParentSetData psd)
	Sets the branching priority of variables. More...

static SCIP_RETCODE	setSpecialProperties (SCIP scip, ParentSetData psd)
	Sets properties to non-standard values. More...

static SCIP_RETCODE	sink_constraint (SCIP scip, ParentSetData psd, int sink)
	Adds a constraint stating that a given node must be a sink This is effected by fixing all parent set indicator variables to zero if the sink is one of the parents. More...

static int	splitAtWhitespace (const char string, char **parts)

Detailed Description

Provides the core functionality for the Bayesian network learning problem.

Function Documentation

◆ addAcyclicityConstraints()

static SCIP_RETCODE addAcyclicityConstraints	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Adds the acyclity constraints to the problem.

Parameters

scip	The SCIP instance to add the constraints to.
psd	The parent set data to use for generating the acyclity constraints.

Returns: SCIP_OKAY if the consraints were all added successfully.

References DC_createCons(), PS_deallocateParentSetData(), and PS_splitToComponents().

Referenced by createBasicModel().

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◆ addAdditionalConstraints()

static SCIP_RETCODE addAdditionalConstraints	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Adds constraints ruling out immoralities in the DAG.

Parameters

scip	The SCIP instance to add the constraint to.
psd	The parent set data associated with this problem.

Returns: SCIP_OKAY if the constraints could be successfully added.Adds optional constraints to the problem based on the parameters in the settings file.

Parameters

scip	The SCIP instance to add the constraint to.
psd	The parent set data associated with this problem.

Returns: SCIP_OKAY if the constraints could be successfully added.

References addEdgeNumberConstraints(), addFounderConstraints(), addGeneralDAGConstraints(), addOrderedCoveredArcConstraints(), addParentNumberConstraints(), PD_addPedigreeSpecificConstraints(), PD_inPedigreeMode(), SCIPcreateConsBasicChordal(), SCIPcreateConsBasicDistinguishedrep(), SCIPcreateConsVanilla(), SCIPincludeConshdlrDistinguishedrep(), and SCIPincludeConshdlrVanilla().

Referenced by BN_readProblem().

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◆ addAncestorVariables()

static SCIP_RETCODE addAncestorVariables	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

If gobnilp/ancestorvars == TRUE, creates binary variables encoding the ancestor relation Creates binary variables anc[i][j] where anc[i][j]==1 iff j is an ancestor of i If gobnilp/useconspartialordering == TRUE, the partial order constraint is used on these variables.

Returns: SCIP_OKAY as long as all is well

Parameters

scip	SCIP data structure
psd	parent sets data structure

References ParentSetData::n, and SCIPcreateConsPartialOrdering().

Referenced by createBasicModel().

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◆ addArrowVariables()

static SCIP_RETCODE addArrowVariables	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Adds variables representing directed and undirected edges The branching priority for these variables is set at 10, so typically SCIP will branch on these variables rather than parent set variables.

Returns: SCIP_OKAY if all is well

Parameters

scip	SCIP data structure
psd	parent sets data structure

References get_arrow(), hashtableCreateArrow(), ParentSetData::n, ParentSetData::nodeNames, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, ParentSetData::PaVars, put_arrow(), and put_edge().

Referenced by createBasicModel().

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◆ addEdgeNumberConstraints()

static SCIP_RETCODE addEdgeNumberConstraints	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Adds constraints on the number of edges in the DAG.

Parameters

scip	The SCIP instance to add the constraint to.
psd	The parent set data associated with this problem.

Returns: SCIP_OKAY if the constraints could be successfully added.

References get_edge(), and ParentSetData::n.

Referenced by addAdditionalConstraints().

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◆ addFounderConstraints()

static SCIP_RETCODE addFounderConstraints	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Adds constraints on the number of possible founders.

Parameters

scip	The SCIP instance to add the constraint to.
psd	The parent set data associated with this problem.

Returns: SCIP_OKAY if the constraints could be successfully added.

References ParentSetData::n, ParentSetData::nParents, ParentSetData::nParentSets, and ParentSetData::PaVars.

Referenced by addAdditionalConstraints().

◆ addGeneralDAGConstraints()

static SCIP_RETCODE addGeneralDAGConstraints	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Adds general structural constraints to the DAG.

Parameters

scip	The SCIP instance to add the constraint to.
psd	The parent set data associated with this problem.

Returns: SCIP_OKAY if the constraints could be successfully added.

References get_edge(), ParentSetData::n, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, ParentSetData::PaVars, and process_constraint().

Referenced by addAdditionalConstraints().

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◆ addImsetVariables()

static SCIP_RETCODE addImsetVariables	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

The imsetvar for a subset of nodes = 1 iff one of the elements in the subset has all the others as parents.

It is binary due to acyclicity. If gobnilp/imsetvars == TRUE, creates and sets the branching priority for, variables representing imsets for subsets of nodes of size 3 Note that the imsetvar for a subset of size 2 is an 'edge' variable - these are always created.

Returns: SCIP_OKAY, if all is well

Parameters

scip	SCIP data structure
psd	parent sets data structure

References get_edge(), ParentSetData::n, ParentSetData::nodeNames, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, and ParentSetData::PaVars.

Referenced by createBasicModel().

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◆ addKBestMECVariables()

static SCIP_RETCODE addKBestMECVariables	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Parameters

scip	SCIP data structure
psd	parent sets data structure

References get_edge(), ParentSetData::n, ParentSetData::nodeNames, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, and ParentSetData::PaVars.

Referenced by createBasicModel().

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◆ addOneParentSetConstraints()

static SCIP_RETCODE addOneParentSetConstraints	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Adds the constraints that there must be one parent set to the problem.

Parameters

scip	The SCIP instance to add the constraints to.
psd	The parent set data to use for generating the constraints.

Returns: SCIP_OKAY if the consraints were all added successfully.

References ParentSetData::n, ParentSetData::nParentSets, and ParentSetData::PaVars.

Referenced by createBasicModel().

◆ addOrderedCoveredArcConstraints()

static SCIP_RETCODE addOrderedCoveredArcConstraints	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Adds constraints ruling out covered arcs from lower to higher vertices.

Parameters

scip	The SCIP instance to add the constraint to.
psd	The parent set data associated with this problem.

Returns: SCIP_OKAY if the constraints could be successfully added.

References differ(), get_arrow(), ParentSetData::n, ParentSetData::nodeNames, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, and ParentSetData::PaVars.

Referenced by addAdditionalConstraints().

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◆ addParentNumberConstraints()

static SCIP_RETCODE addParentNumberConstraints	(	SCIP *	scip,
		const ParentSetData *	psd
	)

static

Adds constraints on the number of nodes that can be parents.

This also requires the creation of a number of binary variables.

Parameters

scip	The SCIP instance to add the constraint to.
psd	The parent set data associated with this problem.

Returns: SCIP_OKAY if the constraints could be successfully added.

References get_arrow(), ParentSetData::n, and ParentSetData::nodeNames.

Referenced by addAdditionalConstraints().

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◆ addParentVariables()

static SCIP_RETCODE addParentVariables	(	SCIP *	scip,
		ParentSetData *	psd,
		SCIP_Real **	scores
	)

static

Creates and adds the parent variables to the problem.

Parameters

scip	The SCIP instance to create the variables for.
psd	The parent set data to base the variables on.
scores	The objective function coefficients for each variable.

Returns: SCIP_OKAY if all variables were successfully created.

References ParentSetData::n, ParentSetData::nodeNames, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, and ParentSetData::PaVars.

Referenced by createBasicModel().

◆ addPaSizeVariables()

static SCIP_RETCODE addPaSizeVariables	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

If gobnilp/pasizevars == TRUE adds and sets the branching priorities of variables representing parent set size.

Creates pasize[i] for each node i which is constrained to be equal to the parent set size of node i

Returns: SCIP_OKAY as long as all is well

Parameters

scip	The SCIP instance
psd	Parent set data

References ParentSetData::n, ParentSetData::nodeNames, ParentSetData::nParents, ParentSetData::nParentSets, and ParentSetData::PaVars.

Referenced by createBasicModel().

◆ addPosindVariables()

static SCIP_RETCODE addPosindVariables	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

If gobnilp/posindvars == TRUE, adds binary variables indicating the position of nodes in a total order consistent with a DAG solution.

Creates n^2 variables posind[i][j], where posind[i][j]==1 iff variable i is in position j in some total order consistent with a DAG solution This is done by the following constraints: pos(j) - pos(i) + n*I(j is a parent of i) =< n-1 pos(i) and pos(j) are integers denoted the index of i and j in a total order. They are defined as a linear combination of posind variables in the obvious way.

Returns: SCIP_OKAY as long as all is well

Parameters

scip	SCIP data structure
psd	parent sets data structure

References get_arrow(), and ParentSetData::n.

Referenced by createBasicModel().

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◆ addPosVariables()

static SCIP_RETCODE addPosVariables	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

If gobnilp/posvars == TRUE, creates integer variables giving a generation number for each node If a node is a founder its generation number is 0 If j is a parent of i its generation number is strictly less than i's An upper bound on any such variable can be set using gobnilp/maxpos Uses an Indicator constraint.

Returns: SCIP_OKAY as long as all is well

Parameters

scip	SCIP data structure
psd	parent sets data structure

References get_arrow(), ParentSetData::n, ParentSetData::nParents, ParentSetData::nParentSets, and ParentSetData::PaVars.

Referenced by createBasicModel().

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◆ addTotalorderVariables()

static SCIP_RETCODE addTotalorderVariables	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

If gobnilp/totalordervars == TRUE, creates, and sets the branching priority for, binary variables encoding a total order consistent with a DAG solution Creates binary variables order[i][j] where order[i][j]==1 if i comes after j in the total ordering.

If gobnilp/useconslinearordering == TRUE, the linear ordering constraint handler that comes as an example with SCIP is used If gobnilp/inittransitivity == TRUE then all n^3 transitivity constraints are added to the problem If gobnilp/bestparentsfororder == TRUE then, for each node, a constraint is added so that the highest scoring parent set consistent with the total order must be selected

Returns: SCIP_OKAY as long as all is well

Parameters

scip	SCIP data structure
psd	parent sets data structure

References get_arrow(), ParentSetData::n, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, ParentSetData::PaVars, and SCIPcreateConsLOP().

Referenced by createBasicModel().

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◆ ancestor_constraint()

static SCIP_RETCODE ancestor_constraint	(	SCIP *	scip,
		ParentSetData *	psd,
		int	i,
		int	j,
		SCIP_Bool	truthvalue
	)

static

Adds a constraint stating that an ancestor relation must be present or absent.

This works by simply fixing the relevant ancestor variable

Parameters

scip	The SCIP instance in which to add the constraint.
psd	The parent set data for the problem.
i	The descendant node
j	The ancestor node
truthvalue	Whether the relation must or must not appear

Returns: SCIP_OKAY if the constraint on the edge was added successfully or an error code otherwise.

Referenced by process_constraint().

◆ BN_addMECNonRepetitionConstraint()

static SCIP_RETCODE BN_addMECNonRepetitionConstraint	(	SCIP *	scip,
		int	run
	)

static

Adds a constraint that prevents networks in the same MEC as the current best network being found again.

Parameters

scip	The SCIP instance being used for the optimisation.
run	The iteration of the loop that this soilution was found on.

Returns: SCIP_OKAY if a constraint could be added, or an error otherwise.

References get_edge(), MD_getParentSetData(), and ParentSetData::n.

Referenced by BN_addNonRepetitionConstraint().

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◆ BN_addNonRepetitionConstraint()

SCIP_RETCODE BN_addNonRepetitionConstraint	(	SCIP *	scip,
		int	run
	)

Adds a constraint that prevents the current best network being found again.

Parameters

scip	The SCIP instance being used for the optimisation.
run	The iteration of the loop that this soilution was found on.

Returns: SCIP_OKAY if a constraint could be added, or an error otherwise.

References BN_addMECNonRepetitionConstraint(), MD_getParentSetData(), ParentSetData::n, ParentSetData::nParentSets, and ParentSetData::PaVars.

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◆ BN_addParameters()

SCIP_RETCODE BN_addParameters ( SCIP * scip )

Adds GOBNILP specific parameters to those recognised by SCIP.

Parameters

scip	The SCIP instance to add to the parameters to.

Returns: SCIP_OKAY if the operation succeeded or an appropriate error coede otherwise.

References IO_addOutputParameters(), PD_addPedigreeParameters(), SC_addScoringParameters(), UT_addBoolParam(), UT_addIntParam(), UT_addLongintParam(), UT_addRealParam(), and UT_addStringParam().

Referenced by main().

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◆ BN_doIterativePrint()

SCIP_RETCODE BN_doIterativePrint	(	SCIP *	scip,
		MA_info *	ma_info,
		int	run
	)

Prints appropriate information about each optimal solution obtained.

Parameters

scip	The SCIP instance for which the solution has been found.
run	The iteration of the main loop that the solution was found on.

Returns: SCIP_OKAY if printing succeeded or an appropriate error code otherwise.

References IO_doIterativePrint(), and MD_getParentSetData().

Referenced by main().

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◆ BN_getNumberOfRepeats()

int BN_getNumberOfRepeats ( SCIP * scip )

Gets the number of most likely Bayesian networks that should be found.

Parameters

scip	The SCIP inatance used for finding the networks.

Returns: The number of Bayesian networks that should be found.

Referenced by main().

◆ BN_includePlugins()

SCIP_RETCODE BN_includePlugins ( SCIP * scip )

Includes all plugins needed by the problem.

Parameters

scip	The SCIP instance to add the plugins to.

Returns: SCIP_OKAY if all plugins were added successfully, or an error otherwise.

References DC_includeConshdlr(), HS_includePrimal(), MD_initialiseMetadata(), SCIPincludeConshdlrChordal(), SCIPincludeConshdlrCi(), SCIPincludeConshdlrLOP(), and SCIPincludeConshdlrPartialOrdering().

Referenced by main().

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◆ BN_printcountsols()

SCIP_RETCODE BN_printcountsols	(	SCIP *	scip,
		char *	filename
	)

Prints solutions found using countsols.

Parameters

scip	The SCIP instance to print scores for.

Returns: SCIP_OKAY if printing succeeded or an error otherwise.

References IO_printcountsols(), and MD_getParentSetData().

Referenced by main().

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◆ BN_printHeader()

SCIP_RETCODE BN_printHeader ( SCIP * scip )

Prints a header which describes the GOBNILP and SCIP systems being used.

Parameters

scip	The SCIP instance that is being used.

Returns: SCIP_OKAY if printing succeeded or an error code otherwise.

References IO_printHeader().

Referenced by main().

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◆ BN_printParameters()

SCIP_RETCODE BN_printParameters ( SCIP * scip )

Prints any of the current SCIP or GOBNILP parameters not at their default value.

Parameters

scip	The SCIP instance to consult the parameters of.

Returns: SCIP_OKAY if the parameters were printed correctly, or an error code otherwise.

References IO_printParameters().

Referenced by main().

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◆ BN_printProblem()

SCIP_RETCODE BN_printProblem	(	SCIP *	scip,
		int	run
	)

Prints the current problem.

Parameters

scip	The SCIP instance for which the problem should be printed.
run	The iteration of the main loop that the problem is to be solved on.

Returns: SCIP_OKAY if printing succeeded or an appropriate error code otherwise.

References IO_printProblem().

Referenced by main().

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◆ BN_printScores()

SCIP_RETCODE BN_printScores ( SCIP * scip )

Prints the scores for the family variables in Jaakkola format.

Parameters

scip	The SCIP instance to print scores for.

Returns: SCIP_OKAY if printing succeeded or an error otherwise.

References IO_printScoresInJKLFormat(), and MD_getParentSetData().

Referenced by main().

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◆ BN_readProblem()

SCIP_RETCODE BN_readProblem	(	SCIP *	scip,
		char *	inputformat,
		char *	frequencyfile,
		const char *	filename
	)

Reads in a problem from a file.

Currently supported file formats are "jak", "cip" and "dat". The one to use is determined using the -f cmmand line argument and the filename extension. See getInputFormat() for details.

Parameters

scip	The SCIP instance to read the problem in to.
filename	The filename from which to read the problem.

Returns: SCIP_OKAY if the problem was successfully created, or an error code otherwise.

References addAdditionalConstraints(), getInputFormat(), MD_getParentSetData(), ParentSetData::n, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, readProblemInCIPFormat(), readProblemInNonCIPFormat(), setBranchingPriorities(), and setSpecialProperties().

Referenced by main().

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◆ BN_setParamaterDefaults()

SCIP_RETCODE BN_setParamaterDefaults ( SCIP * scip )

Sets various built-in SCIP parameters to suitable GOBNILP values.

These values can still be overriden using the settings file.

Parameters

scip	The SCIP instance the parameters relate to.

Returns: SCIP_OKAY if the setting worked or an appropriate error otherwise.

Referenced by main().

◆ BN_suppresscols()

SCIP_RETCODE BN_suppresscols ( SCIP * scip )

Suppresses output columns according to the value of parameter gobnilp/verblevelsetcols.

Returns: SCIP_OKAY assuming all is well

Referenced by main().

◆ ci_constraint()

static SCIP_RETCODE ci_constraint	(	SCIP *	scip,
		ParentSetData *	psd,
		const char *	a_str,
		const char *	b_str,
		const char *	s_str
	)

static

Adds a conditional independence (ci) constraint.

Parameters

scip	The SCIP instance in which to add the constraint.
psd	The parent set data for the problem.
a_str	A set
b_str	B set
s_str	S (separator) set

Returns: SCIP_OKAY if the constraint was added successfully or an error code otherwise.

References ParentSetData::n, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, parseSet(), ParentSetData::PaVars, and SCIPcreateConsCi().

Referenced by process_constraint().

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◆ createBasicModel()

static SCIP_RETCODE createBasicModel	(	SCIP *	scip,
		ParentSetData *	psd,
		SCIP_Real **	scores
	)

static

Adds the variables and constraints needed for the basic DAG learning problem.

Parameters

scip	The SCIP instance to create the problem in.
psd	The parent set data to base the problem on.
scores	The scores of each of the parent sets in the problem.

Returns: SCIP_OKAY if the problem was created successfully.

References addAcyclicityConstraints(), addAncestorVariables(), addArrowVariables(), addImsetVariables(), addKBestMECVariables(), addNChildrenVars(), addOneParentSetConstraints(), addParentVariables(), addPaSizeVariables(), addPosindVariables(), addPosVariables(), and addTotalorderVariables().

Referenced by readProblemInNonCIPFormat().

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◆ differ()

static SCIP_Bool differ	(	SCIP *	scip,
		ParentSetData *	psd,
		int	i,
		int	ki1,
		int	ki2,
		int	j
	)

static

Determines if two parent sets differ by just a single given item.

Parameters

scip	The SCIP instance the variable sets belong to.
psd	The parent set data for the problem.
i	The child variable.
ki1	The index of one parent set of i.
ki2	The index of another parent set of i.
j	A variable.

Returns: True if the parent sets ki1 and ki2 of i are the same except for the presence of variable j in one of them but not the other.

References ParentSetData::nParents, and ParentSetData::ParentSets.

Referenced by addOrderedCoveredArcConstraints().

◆ edge_constraint()

static SCIP_RETCODE edge_constraint	(	SCIP *	scip,
		ParentSetData *	psd,
		int	i,
		int	j,
		SCIP_Bool	undirected,
		SCIP_Bool	truthvalue
	)

static

Adds a constraint stating that an edge must be present or absent.

This works by simply fixing the relevant edge or arrow variable

Parameters

scip	The SCIP instance in which to add the constraint.
psd	The parent set data for the problem.
i	The node from which the edge starts.
j	The node at which the edge finishes.
undirected	Whether the edge is undirected or not.
truthvalue	Whether the edge must or must not appear

Returns: SCIP_OKAY if the constraint on the edge was added successfully or an error code otherwise.

References get_arrow(), and get_edge().

Referenced by process_constraint().

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◆ getDelimiters()

static SCIP_RETCODE getDelimiters	(	SCIP *	scip,
		int *	num_delims,
		char **	delims,
		SCIP_Bool *	merge_delims
	)

static

Gets the delimiter information needed to read in information from files.

Parameters

scip	The SCIP instance being used.
num_delims	The number of delimiters.
delims	The delimiters to use.
merge_delims	Whether consecutive delimiters should be merged into one.

Returns: SCIP_OKAY if the parameters were successfully read, or an error otherwise.

Referenced by readProblemInNonCIPFormat().

◆ getInputFormat()

static char* getInputFormat	(	SCIP *	scip,
		char *	inputformat,
		const char *	filename
	)

static

Gets the format in which the input file has been given.

If the format has been set on the command line, this will be given. If this is not set, then the suffix of the filename will be examined. If this does not work, then DEFAULT_GOBNILP_PARAMS_FILE is used.

Parameters

scip	The SCIP instance this applies to.
filename	The name of the file to read.

Returns: The format of the input file.

Referenced by BN_readProblem().

◆ getProblemName()

static SCIP_RETCODE getProblemName	(	const char *	filename,
		char *	probname,
		int	maxSize
	)

static

Gets a problem name based on the file from which it was read.

This function copied from LOP example written by March Pfetsch.

Returns: SCIP_OKAY if the name could be found. An error otherwise.

Parameters

filename	input filename
probname	output problemname
maxSize	maximum size of probname

Referenced by readProblemInNonCIPFormat().

◆ immorality_constraint()

static SCIP_RETCODE immorality_constraint	(	SCIP *	scip,
		ParentSetData *	psd,
		int	i,
		int	j,
		int	child,
		SCIP_Bool	truthvalue
	)

static

Adds a constraint enforcing or preventing an immorality constraint.

Parameters

scip	The SCIP instance in which to add the constraint.
psd	The parent set data for the problem.
i	A parent involved in the immorality constraint.
j	The other parent involved.
child	The child involved in the constraint.
truthvalue	TRUE if the immorality must exist, FALSE if it must not exist.

Returns: SCIP_OK if the constraint was added, or an error code otherwise.

References get_edge(), ParentSetData::nodeNames, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, and ParentSetData::PaVars.

Referenced by process_constraint().

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◆ order_constraint()

static SCIP_RETCODE order_constraint	(	SCIP *	scip,
		ParentSetData *	psd,
		int	i,
		int	j
	)

static

Adds a constraint stating that variable i must come before variable j in any variable ordering consistent with the learned network This works by simply fixing the relevant total order variable An error is generated if the user has not asked for the total order constraint handler to be used.

Parameters

scip	The SCIP instance in which to add the constraint.
psd	The parent set data for the problem.
i	The node which must be earlier in the order.
j	The node which must be later in the order.

Returns: SCIP_OKAY if the constraint on the edge was added successfully or an error code otherwise.

Referenced by process_constraint().

◆ parseSet()

static SCIP_RETCODE parseSet	(	SCIP *	scip,
		ParentSetData *	psd,
		const char *	str,
		int *	set,
		int *	n_set,
		SCIP_Bool *	success
	)

static

Parses a string to extract a set from it.

Parameters

scip	The SCIP instance that this belongs to.
psd	The data set that the set refers to.
str	string to parse
set	result set
n_set	length of set
success	success flag

References get_index().

Referenced by ci_constraint().

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◆ process_constraint()

static SCIP_RETCODE process_constraint	(	SCIP *	scip,
		ParentSetData *	psd,
		const char *	line
	)

static

Adds a constraint on the DAG structure.

Parameters

scip	The SCIP instance in which to add the constraint.
psd	The parent set data relating to this problem.
line	The description of the constraint to add.

Returns: SCIP_OKAY if the constraint was added or an error otherwise.

References ancestor_constraint(), ci_constraint(), edge_constraint(), get_index(), immorality_constraint(), order_constraint(), and sink_constraint().

Referenced by addGeneralDAGConstraints().

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◆ readProblemInCIPFormat()

static SCIP_RETCODE readProblemInCIPFormat	(	SCIP *	scip,
		const char *	filename
	)

static

Reads a problem from a file in cip format.

Parameters

scip	The SCIP instance in to which the problem should be read.
filename	The file to read the problem from.

Returns: SCIP_OKAY if the problem was successfully created, or an error code otherwise.

Referenced by BN_readProblem().

◆ readProblemInJaakkolaFormat()

static SCIP_RETCODE readProblemInJaakkolaFormat	(	SCIP *	scip,
		const char *	filename,
		ParentSetData *	psd,
		SCIP_Real ***	scores,
		PropertyData *	prop
	)

static

Reads local score BN file (in Jaakkola format)

Format:

first line is: number of variables then local scores for each variable
first line of section of local scores is "variable number_of_parent_sets"
other lines are like "score 3 parent1 parent2 parent3" (e.g. when there are 3 parents)

Parameters

scip	The SCIP instance being used.
filename	The file to read from.
psd	The parentage data that is read from the file.
scores	The score of each of the parent set combinations.
prop	The properties of the data read from the file.

Returns: SCIP_OKAY if reading was successful, or an appropriate error code otherwise.

References ParentSetData::n, PropertyData::n, ParentSetData::nodeNames, ParentSetData::nParents, ParentSetData::nParentSets, PropertyData::num_properties, ParentSetData::ParentSets, PropertyData::property_names, and PropertyData::property_values.

Referenced by readProblemInNonCIPFormat().

◆ readProblemInNonCIPFormat()

static SCIP_RETCODE readProblemInNonCIPFormat	(	SCIP *	scip,
		char *	frequencyfile,
		const char *	filename,
		char *	format
	)

static

Reads a problem from a file in a format other than CIP.

Parameters

scip	The SCIP instance in to which the problem should be read.
filename	The file to read the problem from.
format	The format the problem is given in.

Returns: SCIP_OKAY if the problem was successfully created, or an error code otherwise.

References createBasicModel(), getDelimiters(), getProblemName(), IO_printScoresInJKLFormat(), MD_setParentSetData(), MD_setPropertyData(), ParentSetData::n, ParentSetData::nodeNames, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, ParentSetData::PaVars, PR_deallocatePropertyData(), PR_initialise(), PS_readProblemInGenomeFormat(), readProblemInJaakkolaFormat(), readProblemInPSSFormat(), and SC_readProblemInDataFormat().

Referenced by BN_readProblem().

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◆ readProblemInPSSFormat()

static SCIP_RETCODE readProblemInPSSFormat	(	SCIP *	scip,
		const char *	filename,
		ParentSetData *	psd,
		SCIP_Real ***	scores,
		PropertyData *	prop
	)

static

Reads local score BN file (in PSS format)

Parameters

scip	The SCIP instance being used.
filename	The file to read from.
psd	The parentage data that is read from the file.
scores	The score of each of the parent set combinations.
prop	The properties of the data read from the file.

Returns: SCIP_OKAY if reading was successful, or an appropriate error code otherwise.

Referenced by readProblemInNonCIPFormat().

◆ setBranchingPriorities()

static SCIP_RETCODE setBranchingPriorities	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Sets the branching priority of variables.

Parameters

scip	The SCIP instance being used.
psd	The data for the problem.

References get_arrow(), get_edge(), ParentSetData::n, ParentSetData::nParentSets, and ParentSetData::PaVars.

Referenced by BN_readProblem().

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◆ setSpecialProperties()

static SCIP_RETCODE setSpecialProperties	(	SCIP *	scip,
		ParentSetData *	psd
	)

static

Sets properties to non-standard values.

Parameters

scip	The SCIP instance being used.
psd	The data for the problem.

References get_arrow(), get_edge(), ParentSetData::n, ParentSetData::nParentSets, and ParentSetData::PaVars.

Referenced by BN_readProblem().

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◆ sink_constraint()

static SCIP_RETCODE sink_constraint	(	SCIP *	scip,
		ParentSetData *	psd,
		int	sink
	)

static

Adds a constraint stating that a given node must be a sink This is effected by fixing all parent set indicator variables to zero if the sink is one of the parents.

Parameters

scip	The SCIP instance in which to add the constraint.
psd	The parent set data for the problem.
sink	The node which must be a sink.

Returns: SCIP_OKAY if the constraint on the edge was added successfully or an error code otherwise.

References ParentSetData::n, ParentSetData::nParents, ParentSetData::nParentSets, ParentSetData::ParentSets, and ParentSetData::PaVars.

Referenced by process_constraint().

Macros

Functions

Detailed Description

Function Documentation

◆ addAcyclicityConstraints()

◆ addAdditionalConstraints()

◆ addAncestorVariables()

◆ addArrowVariables()

◆ addEdgeNumberConstraints()

◆ addFounderConstraints()

◆ addGeneralDAGConstraints()

◆ addImsetVariables()

◆ addKBestMECVariables()

◆ addOneParentSetConstraints()

◆ addOrderedCoveredArcConstraints()

◆ addParentNumberConstraints()

◆ addParentVariables()

◆ addPaSizeVariables()

◆ addPosindVariables()

◆ addPosVariables()

◆ addTotalorderVariables()

◆ ancestor_constraint()

◆ BN_addMECNonRepetitionConstraint()

◆ BN_addNonRepetitionConstraint()

◆ BN_addParameters()

◆ BN_doIterativePrint()

◆ BN_getNumberOfRepeats()

◆ BN_includePlugins()

◆ BN_printcountsols()

◆ BN_printHeader()

◆ BN_printParameters()

◆ BN_printProblem()

◆ BN_printScores()

◆ BN_readProblem()

◆ BN_setParamaterDefaults()

◆ BN_suppresscols()

◆ ci_constraint()

◆ createBasicModel()

◆ differ()

◆ edge_constraint()

◆ getDelimiters()

◆ getInputFormat()

◆ getProblemName()

◆ immorality_constraint()

◆ order_constraint()

◆ parseSet()

◆ process_constraint()

◆ readProblemInCIPFormat()

◆ readProblemInJaakkolaFormat()

◆ readProblemInNonCIPFormat()

◆ readProblemInPSSFormat()

◆ setBranchingPriorities()

◆ setSpecialProperties()

◆ sink_constraint()