Package edu.cmu.tetrad.search.work_in_progress

Class ISBDeuScore

java.lang.Object

edu.cmu.tetrad.search.work_in_progress.ISBDeuScore

All Implemented Interfaces:

ISScore

public class ISBDeuScore
extends Object
implements ISScore

Added by Fattaneh Calculates the Instance-Specific BDeu score.

Constructor Summary

Constructors

Constructor	Description
ISBDeuScore(DataSet dataSet, DataSet testCase)	Initializes the ISBDeuScore with the given dataset and test case.

Method Summary

Modifier and Type	Method	Description
boolean	determines(List<Node> z, Node y)	Determines whether a given node y is determined by a list of nodes z.
DataSet	getDataSet()	Retrieves a DataSet object.
double	getKAddition()	Retrieves the value of the variable representing the k_addition.
double	getKDeletion()	Retrieves the value of the k_deletion field.
double	getKReorientation()	Retrieves the value of the k_reorient variable.
int	getMaxDegree()	Calculates the maximum degree based on the sample size.
int[]	getParentValues(int nodeIndex, int rowIndex, int[] dims)	Computes the parent values for a given node index and row index according to the specified dimensions.
int[]	getParentValuesForCombination(int rowIndex, int[] dims)	Calculates the parent values for a given combination of dimensions.
double	getSamplePrior()	Retrieves the prior value of the sample.
int	getSampleSize()	Retrieves the current sample size.
double	getStructurePrior()	Retrieves the value of the structure prior.
Node	getVariable(String targetName)	Retrieves a Node from the variables list that matches the specified target name.
List<Node>	getVariables()	Retrieves the list of variables associated with this instance.
boolean	isEffectEdge(double bump)	Must be called directly after the corresponding scoring call.
double	localScore(int node, int[] parents_is, int[] parents_pop, int[] children_pop)	Calculates the local score for a given node in the context of its parent nodes and children population.
double	localScore1(int node, int[] parents_is, int[] parents_pop, int[] children_pop)	Computes the local score for a given node considering both population and context-specific parents.
double	localScoreDiff(int x, int y, int[] z, int[] z_pop, int[] child_pop)	Computes the difference in local scores when element x is appended to the array z.
void	setKAddition(double k_addition)	Sets the value of k_addition.
void	setKDeletion(double k_deletion)	Sets the value of k_deletion.
void	setKReorientation(double k_reorient)	Sets the value of the K-reorientation parameter.
void	setSamplePrior(double samplePrior)	Sets the value for the samplePrior field.
void	setStructurePrior(double structurePrior)	Sets the structure prior for the model.
void	setVariables(List<Node> variables)	Sets the list of variables after validating that each variable in the provided list has the same name as the corresponding variable in the existing list.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

ISBDeuScore

public ISBDeuScore(DataSet dataSet,
 DataSet testCase)

Initializes the ISBDeuScore with the given dataset and test case.

Parameters:

dataSet - the dataset to be used for scoring. Must not be null.

testCase - the test case to evaluate. Must not be null.

Throws:

NullPointerException - if either dataSet or testCase is null.

Method Details

localScore

public double localScore(int node,
 int[] parents_is,
 int[] parents_pop,
 int[] children_pop)

Description copied from interface: ISScore

Calculates the local score for a given node in the context of its parent nodes and children population.

Specified by:

localScore in interface ISScore

Parameters:

node - The index of the node for which the score is being calculated.

parents_is - An array representing the indices of the parent nodes.

parents_pop - An array representing the population of the parent nodes.

children_pop - An array representing the population of the children nodes.

Returns:

The local score for the specified node.

getParentValues

public int[] getParentValues(int nodeIndex,
 int rowIndex,
 int[] dims)

Computes the parent values for a given node index and row index according to the specified dimensions.

Parameters:

nodeIndex - The index of the node for which parent values are computed.

rowIndex - The row index used for computations.

dims - An array representing the dimensions of the parent values.

Returns:

An array of integers representing the computed parent values.

getParentValuesForCombination

public int[] getParentValuesForCombination(int rowIndex,
 int[] dims)

Calculates the parent values for a given combination of dimensions.

Parameters:

rowIndex - the index representing the combination in a linearized form

dims - an array indicating the size of each dimension

Returns:

an array of integers where each element corresponds to the value of the dimension at that index

localScoreDiff

public double localScoreDiff(int x,
 int y,
 int[] z,
 int[] z_pop,
 int[] child_pop)

Computes the difference in local scores when element x is appended to the array z.

Specified by:

localScoreDiff in interface ISScore

Parameters:

x - the element to be appended to the array z

y - the dependent variable whose score is being calculated

z - the initial array of elements

z_pop - the population related to z

child_pop - the population related to the dependent variable y

Returns:

the difference in local scores after appending x to z

getVariables

public List<Node> getVariables()

Retrieves the list of variables associated with this instance.

Specified by:

getVariables in interface ISScore

Returns:

a list of Node objects representing the variables

setVariables

public void setVariables(List<Node> variables)

Sets the list of variables after validating that each variable in the provided list has the same name as the corresponding variable in the existing list.

Parameters:

variables - a list of Node objects to be set as the new variables

Throws:

IllegalArgumentException - if any variable in the provided list does not have the same name as the variable it is replacing

getSampleSize

public int getSampleSize()

Retrieves the current sample size.

Specified by:

getSampleSize in interface ISScore

Returns:

the sample size as an integer.

isEffectEdge

public boolean isEffectEdge(double bump)

Must be called directly after the corresponding scoring call.

Specified by:

isEffectEdge in interface ISScore

Parameters:

bump - The threshold value to evaluate the significance of the effect on the edge.

Returns:

true if the edge has a significant effect; false otherwise.

getDataSet

public DataSet getDataSet()

Retrieves a DataSet object.

Specified by:

getDataSet in interface ISScore

Returns:

a DataSet object

Throws:

UnsupportedOperationException - if the method is not supported

getStructurePrior

public double getStructurePrior()

Retrieves the value of the structure prior.

Specified by:

getStructurePrior in interface ISScore

Returns:

the structure prior as a double.

setStructurePrior

public void setStructurePrior(double structurePrior)

Sets the structure prior for the model.

Specified by:

setStructurePrior in interface ISScore

Parameters:

structurePrior - the prior value to be set, typically controlling the influence of structure in the model

getSamplePrior

public double getSamplePrior()

Retrieves the prior value of the sample.

Specified by:

getSamplePrior in interface ISScore

Returns:

the prior value of the sample as a double.

setSamplePrior

public void setSamplePrior(double samplePrior)

Sets the value for the samplePrior field.

Specified by:

setSamplePrior in interface ISScore

Parameters:

samplePrior - The prior sample value to be set.

getKAddition

public double getKAddition()

Retrieves the value of the variable representing the k_addition.

Returns:

the current value of the k_addition variable as a double.

setKAddition

public void setKAddition(double k_addition)

Sets the value of k_addition.

Parameters:

k_addition - The value to set for k_addition.

getKDeletion

public double getKDeletion()

Retrieves the value of the k_deletion field.

Returns:

the current value of k_deletion.

setKDeletion

public void setKDeletion(double k_deletion)

Sets the value of k_deletion.

Parameters:

k_deletion - the new value to set for k_deletion

getKReorientation

public double getKReorientation()

Retrieves the value of the k_reorient variable.

Returns:

The value of k_reorient as a double.

setKReorientation

public void setKReorientation(double k_reorient)

Sets the value of the K-reorientation parameter.

Parameters:

k_reorient - the new value for the K-reorientation parameter

getVariable

public Node getVariable(String targetName)

Retrieves a Node from the variables list that matches the specified target name.

Specified by:

getVariable in interface ISScore

Parameters:

targetName - the name of the target Node to be retrieved

Returns:

the Node that matches the target name, or null if no match is found

getMaxDegree

public int getMaxDegree()

Calculates the maximum degree based on the sample size.

Specified by:

getMaxDegree in interface ISScore

Returns:

the maximum degree as an integer.

determines

public boolean determines(List<Node> z,
 Node y)

Determines whether a given node y is determined by a list of nodes z.

Specified by:

determines in interface ISScore

Parameters:

z - the list of nodes to be evaluated

y - the node to be checked

Returns:

true if y is determined by the list of nodes z, false otherwise

localScore1

public double localScore1(int node,
 int[] parents_is,
 int[] parents_pop,
 int[] children_pop)

Computes the local score for a given node considering both population and context-specific parents.

This function is used to score a node in a dag without using structure prior

Specified by:

localScore1 in interface ISScore

Parameters:

node - The index of the node for which the score is being calculated.

parents_is - Array representing the indices of the context-specific parents.

parents_pop - Array representing the indices of the population-based parents.

children_pop - Array representing the indices of the population-based children.

Returns:

The computed local score for the specified node.