com.bayesia.api

Class APIInference

java.lang.Object

com.bayesia.api.APIInference

All Implemented Interfaces:

java.io.Closeable, java.lang.AutoCloseable

public class APIInference
extends java.lang.Object
implements java.io.Closeable

The class APIInference is used to perform exact or approximate inference on a bayesian network. The bayesian network is loaded from an xbl file. This format is generated by BayesiaLab from Bayesia.

The exact inference is performed with a junction tree algorithm. The approximate inference is performed with a likelihood weighting algorithm.

The class APIInference allows using networks containing discrete, interval, constraint and utility nodes. It allows also the use of temporal or dynamic networks.

All the methods of this class can throw an instance of IllegalOperationException which is a subclass of RuntimeException so you can avoid to catch them.

Version:

4.2

Author:

Bayesia S.A.S.

Field Summary

Fields

Modifier and Type	Field and Description
static int	APPROXIMATE_INFERENCE
static int	EXACT_INFERENCE
static int	NONE_VALUE

Constructor Summary

Constructors

Constructor and Description
APIInference(BayesianNetworkTransferHandler networkHandler, java.lang.String licenseKey, int inferenceType) Creates a new APIInference with the network stored in the specified BayesianNetworkTransferHandler.
APIInference(BayesianNetworkTransferHandler networkHandler, java.lang.String licenseServerHost, int licenseServerPort, java.lang.String userName, java.lang.String password, java.lang.String account, int inferenceType) Creates a new APIInference with the network stored in the specified BayesianNetworkTransferHandler.
APIInference(java.io.InputStream stream, java.lang.String licenseKey, int inferenceType) Creates a new APIInference with the network read from the specified InputStream.
APIInference(java.io.InputStream stream, java.lang.String licenseServerHost, int licenseServerPort, java.lang.String userName, java.lang.String password, java.lang.String account, int inferenceType) Creates a new APIInference with the network read from the specified InputStream.
APIInference(java.lang.String fileName, java.lang.String licenseKey, int inferenceType) Creates a new APIInference with the network stored in the specified file.
APIInference(java.lang.String fileName, java.lang.String licenseServerHost, int licenseServerPort, java.lang.String userName, java.lang.String password, java.lang.String account, int inferenceType) Creates a new APIInference with the network stored in the specified file.

Method Summary

Modifier and Type	Method and Description
void	close() Method used to close the current instance of APIInference.
boolean	containsClass(java.lang.String className) Tests if a class with the given name exists in the network
boolean	containsNode(java.lang.String nodeName) Tests if a node with the given name exists in the network
BayesianNetworkTransferHandler	exportNetwork(java.lang.String networkName) Exports the network and its associated junction tree (if the inference type is EXACT_INFERENCE) with the specified name into a BayesianNetworkTransferHandler in order to used it with the APIInference, APIModeling or APILearningfor example.
java.lang.String	getArcComment(java.lang.String nodeName1, java.lang.String nodeName2) Returns the html comment associated to the arc between the nodes named nodeName1 and nodeName2.
java.lang.String	getArcCommentAsString(java.lang.String nodeName1, java.lang.String nodeName2) Returns the comment string associated to the arc between the nodes named nodeName1 and nodeName2.
int	getArcOrientationBetween(java.lang.String nodeName1, java.lang.String nodeName2) Returns the orientation of the arc between nodeName1 and nodeName2.
ResizableIcon	getBackgroundImage() Gets the image associated to the network.
java.lang.String[]	getChildren(java.lang.String nodeName) Returns the name of the children of the specified node
java.lang.String[]	getClasses() Returns an array containing the name of the classes declared in the network.
java.lang.String[]	getClassNodes(java.lang.String className) Returns an array containing the list of the node belonging to the given class.
java.lang.String	getComment() Returns the html comment associated to the network.
java.lang.Double[]	getCompletedStateValues(java.lang.String nodeName) Returns an array of Double with a value or null for each state of the node.
java.lang.String[]	getConstraintNodeNames() Returns the list of the names of constraint nodes.
java.lang.String[]	getContinuousNodeNames() Returns the list of the names of simple continuous nodes (neither discrete nor constraint nor decision nor utility nor function).
int	getCurrentTime() Returns the current time of the network.
java.lang.String[]	getDecisionNodeNames() Returns the list of the names of decision nodes.
java.lang.String[]	getDiscreteNodeNames() Returns the list of the names of simple discrete nodes (neither interval nor constraint nor decision nor utility nor function).
short	getFilteredIndex(java.lang.String nodeName) Returns the index of the filtered state of the specified node or -1 if the node does not have a filtered state.
java.lang.String	getFilteredState(java.lang.String nodeName) Returns the name of the filtered state of the specified node or null if the node does not have a filtered state.
java.lang.String	getFormula(java.lang.String nodeName) Returns the formula associated to the node as String.
java.lang.String[]	getFunctionNodeNames() Returns the list of the names of function nodes.
FunctionValue	getFunctionValue(java.lang.String nodeName) Returns the value of a function node as an instance of FunctionValue.
double[]	getGlobalUtility() Returns an array containing the sum of the minimum utilities, the sum of the current utilities and the sum of the maximum utilities of all utility nodes.
int	getInferenceType() Returns APPROXIMATE_INFERENCE if the inference type is approximate or EXACT_INFERENCE if the inference type is exact.
short	getIntervalForValue(java.lang.String nodeName, double value) Retrieves the index of the interval corresponding to the specified double value for an continuous node only.
double[][]	getIntervals(java.lang.String nodeName) Returns an array containing the minimum and the maximum of each interval of the node as doubles.
int[]	getIntValues(java.lang.String nodeName) Returns an array containing the states of the node as integers if the node is an integer node.
double	getJointProbability() Return the joint probability of the network according to the evidence set.
double	getLikelihood(java.lang.String nodeName, java.lang.String value) Returns the likelihood associated to a value of a node.
double[]	getLikelihoods(java.lang.String nodeName) Retrieves an array containing the likelihoods associated to the values of a node.
static double	getMean(java.lang.Double[] values, double[] probabilities) Computes the mean given the values and the probability distribution.
double	getMean(java.lang.String nodeName) Returns the mean of a node.
double[]	getMinXEntProbabilities(java.lang.String nodeName, double[] initialProbabilities, double targetMean) Try to find the best probability distribution to obtain the target mean starting from the given initial probabilities, minimizing cross-entropy.
java.lang.String	getName() Returns the name of the loaded network.
java.lang.String[]	getNodeClasses(java.lang.String nodeName) Returns the classes of which the given node is associated.
java.awt.Color	getNodeColor(java.lang.String nodeName) Returns the Color associated to the node or null if there is no associated color.
java.lang.String	getNodeComment(java.lang.String nodeName) Returns the html comment associated to the specified node
java.lang.String	getNodeCommentAsString(java.lang.String nodeName) Returns the comment string associated to the specified node
java.lang.Double	getNodeCost(java.lang.String nodeName) Returns the cost associated to the node or null if there is no cost.
short	getNodeFilteredState(java.lang.String nodeName) Returns the index of the node's filtered state.
ResizableIcon	getNodeImage(java.lang.String nodeName) Gets the image as an instance of ResizableIcon associated to the node or null if there is no associated image.
java.lang.String	getNodeLongName(java.lang.String nodeName) Return the long name associated to the specified node or null if there is no long name
java.lang.String[]	getNodeNames() Returns an array containing the name of the nodes in the network
int	getNodeNumber() Returns the number of nodes in the network
java.awt.geom.Point2D	getNodePosition(java.lang.String nodeName) Returns the position of the center of the node as a point with double precision.
short	getNodeReferenceState(java.lang.String nodeName) Returns the index of the node's reference state.
short	getObservedIndex(java.lang.String nodeName) Returns the index of the observed state of the specified node if the node is hard observed.
java.lang.Double	getObservedMean(java.lang.String nodeName) Returns the target mean of the specified node if the node is mean observed.
double[]	getObservedProbabilities(java.lang.String nodeName) Returns the target probabilities of the specified node if the node is probability observed.
java.lang.String	getObservedValue(java.lang.String nodeName) Returns the observed value of the specified node if the node is hard observed.
java.lang.String[]	getParents(java.lang.String nodeName) Returns the name of the parents of the specified node
double[]	getProbabilities(java.lang.String nodeName) Return the posterior probabilities associated to the values of the specified node.
double	getProbability(java.lang.String nodeName, java.lang.String value) Returns the probability associated to a specific value of a node.
double[]	getQualities(java.lang.String nodeName) Returns an array containing the qualities of a decision node. it can be used only on a decision node.
double[]	getRealValues(java.lang.String nodeName) Returns an array containing the states of the node as doubles if all the node's values are real numberss.
int	getSampleSize() Returnss the sample size used to perform the approximate inference.
java.lang.String[]	getSortedNodeNames(APIUtils.NODE_SORTING_METHOD sortingMethod, boolean increase) Return an array containing the name of the nodes in the network sorted according to the APIUtils.NODE_SORTING_METHOD
static double	getStandardDeviation(double mean, java.lang.Double[] values, double[] probabilities) Computes the standard deviation given a mean, the values and the probability distribution.
double	getStandardDeviation(java.lang.String nodeName) Returns the standard deviation of a node.
java.lang.String[]	getStandardNodeNames() Returns the list of the names of standard chance nodes (neither constraint nor decision nor utility nor function).
int	getStateCount(java.lang.String nodeName) Returns the number of states of the specified node.
java.lang.String	getStateLongNameAt(java.lang.String nodeName, int state) Returns the long names of a given state for a given node.
java.lang.String[]	getStateLongNames(java.lang.String nodeName) Returns an array of String containing the long name for each state of the specified node.
java.lang.Double	getStateValueAt(java.lang.String nodeName, int state) Returns the value associated to the given state of the given node.
java.lang.Double[]	getStateValues(java.lang.String nodeName) Returns an array of Double containing the values associated to each state of the given node.
java.lang.String	getStringComment() Returns the comment as string associated to the network.
java.lang.String[]	getStringValues(java.lang.String nodeName) Returns an array containing the states of the node as String .
java.lang.String	getTargetNodeName() Returns the name of the target node of the network.
short	getTargetState() Returns the target state of the target node
double[]	getUtility(java.lang.String nodeName) Returns an array containing the minimum utility, the current utility and the maximum utility of a utility node. it can be used only on a utility node.
java.lang.String[]	getUtilityNodeNames() Returns the list of the names of utility nodes.
java.lang.Double[]	getValues(java.lang.String nodeName) Returns the values associated to the states of the specified node.
boolean	hasArcBetween(java.lang.String nodeName1, java.lang.String nodeName2) Tests if there is an arc between the specified nodes
boolean	hasConstraintNodes() Tests if the networks contains constraint nodes.
boolean	hasContinuousNodes() Tests if the networks contains continuous nodes (neither discrete nor constraint nor decision nor utility nor function).
boolean	hasDecisionNodes() Tests if the networks contains decision nodes.
boolean	hasDiscreteNodes() Tests if the networks contains simple discrete nodes (neither interval nor constraint nor decision nor utility nor function).
boolean	hasFilteredState(java.lang.String nodeName) Tests if the specified node has a filtered state.
boolean	hasFunctionNodes() Tests if the networks contains function nodes.
boolean	hasStandardNodes() Tests if the networks contains standard chance nodes (neither constraint nor decision nor utility nor function).
boolean	hasTargetNode() Tests if the network has a target node defined
boolean	hasTemporalArcBetween(java.lang.String nodeName1, java.lang.String nodeName2) Tests if there is a temporal arc between the specified chance nodes
boolean	hasUtilityNodes() Tests if the networks contains utility nodes.
void	increaseTime() Performs a step of temporal simulation : from getCurrentTime() to getCurrentTime()+1.
boolean	isBoolean(java.lang.String nodeName) Tests if the specified node is boolean, i.e. its values are equivalent to true and false.
boolean	isChildOf(java.lang.String nodeName1, java.lang.String nodeName2) Tests if there is an arc from nodeName2 to nodeName1
boolean	isConstraint(java.lang.String nodeName) Tests if the node is a constraint node.
boolean	isDecision(java.lang.String nodeName) Tests if the node is a decision node.
boolean	isFunction(java.lang.String nodeName) Tests if the node is a function node.
boolean	isHardObserved(java.lang.String nodeName) Returns true if the node has hard evidence set, i.e. a state if observed.
boolean	isInteger(java.lang.String nodeName) Tests if all the values of the specified node are integers.
boolean	isInterval(java.lang.String nodeName) Tests if the node is described by a list of consecutives intervals.
boolean	isLikelihoodObserved(java.lang.String nodeName) Returns true if the node is observed with likelihoods.
boolean	isMeanObserved(java.lang.String nodeName) Returns true if the node is observed with target mean.
boolean	isObservationValidityEnabled() Returns the state of the observation validity checking.
boolean	isObserved(java.lang.String nodeName) Tests if the specified node is observed.
boolean	isObservedMeanBinary(java.lang.String nodeName) Returns true if the distribution used to compute the mean is binary, false if the distribution is generated by MinXEnt.
boolean	isParentOf(java.lang.String nodeName1, java.lang.String nodeName2) Tests if there is an arc from nodeName1 to nodeName2
boolean	isProbabilityObserved(java.lang.String nodeName) Returns true if the node is observed with target probabilities.
boolean	isReal(java.lang.String nodeName) Tests if all the values of the specified node are reals.
boolean	isStandard(java.lang.String nodeName) Tests if the node is a standard chance node (neither constraint nor decision nor utility nor function).
boolean	isTemporal() Tests if the network is temporal.
boolean	isUtility(java.lang.String nodeName) Tests if the node is a utility node.
boolean	nodeContainsClass(java.lang.String nodeName, java.lang.String className) Tests if a class with the given name exists in the given node
boolean	observe(java.lang.String nodeName, double value) Observes a double value for an interval node only.
boolean	observe(java.lang.String nodeName, short valueIndex) Observes a value through its index for a node.
boolean	observe(java.lang.String nodeName, java.lang.String value) Observes a value for a node.
void	resetTime() Resets the time to 0.
void	save(java.io.OutputStream stream) Saves the created network and its associated junction tree (if the inference type is EXACT_INFERENCE) into the specified OutputStream.
void	save(java.lang.String path) Saves the created network and its associated junction tree (if the inference type is EXACT_INFERENCE) into the file specified by the given path.
void	setInferenceType(int type) Sets the type of inference to use.
boolean	setLikelihood(java.lang.String nodeName, short valueIndex, double likelihood) Sets the likelihood for a value of a node (soft evidence).
boolean	setLikelihood(java.lang.String nodeName, java.lang.String value, double likelihood) Sets the likelihood for a value of a node (soft evidence).
boolean	setLikelihoodFromMean(java.lang.String nodeName, double mean, boolean binaryDistribution) Computes the likelihood for all the values of a node in order to have its mean equal to the specified one.
boolean	setLikelihoodFromProbabilities(java.lang.String nodeName, double[] probabilities) Computes the likelihood for all the values of a node in order to have its probabilities equal to the specified ones.
boolean	setLikelihoods(java.lang.String nodeName, double[] likelihoods) Sets the likelihoods for all the values of a node.
void	setObservationValidityEnabled(boolean b) Sets the observation validity enabled or not.
boolean	setObservedMean(java.lang.String nodeName, double mean, boolean binaryDistribution) Computes the likelihood for all the values of a node in order to have its mean equal to the specified one.
boolean	setObservedProbabilities(java.lang.String nodeName, double[] probabilities) Computes the likelihood for all the values of a node in order to have its probabilities equal to the specified ones.
void	setSampleSize(int sampleSize) Sets the sample size used by approximate inference.
void	setTargetNode(java.lang.String nodeName, short state) Set the given node as target node with the given target state.
void	setTime(int time) Performs a temporal simulation from the current time to the specified time.
void	unobserve(java.lang.String nodeName) Unobserves the specified node.
void	unobserveAll() Unobserves all the nodes.

Methods inherited from class java.lang.Object

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

Field Detail

EXACT_INFERENCE

public static final int EXACT_INFERENCE

See Also:

Constant Field Values

APPROXIMATE_INFERENCE

public static final int APPROXIMATE_INFERENCE

See Also:

Constant Field Values

NONE_VALUE

public static final int NONE_VALUE

See Also:

Constant Field Values

Constructor Detail

APIInference

public APIInference(java.io.InputStream stream,
                    java.lang.String licenseKey,
                    int inferenceType)

Creates a new APIInference with the network read from the specified InputStream. You must provide a valid licence key for inference.

Parameters:

stream - the stream of the xbl file containing the network

licenseKey - the key of the licence.

inferenceType - one of EXACT_INFERENCE and APPROXIMATE_INFERENCE.

APIInference

public APIInference(java.lang.String fileName,
                    java.lang.String licenseKey,
                    int inferenceType)

Creates a new APIInference with the network stored in the specified file. You must provide a valid licence key for inference.

Parameters:

fileName - the name of the xbl file containing the network

licenseKey - the key of the licence.

inferenceType - one of EXACT_INFERENCE and APPROXIMATE_INFERENCE.

APIInference

public APIInference(java.io.InputStream stream,
                    java.lang.String licenseServerHost,
                    int licenseServerPort,
                    java.lang.String userName,
                    java.lang.String password,
                    java.lang.String account,
                    int inferenceType)

Creates a new APIInference with the network read from the specified InputStream. You must provide the host and the port of the license server. You must provide also the user name and the password of an access added to the license. This access must be associated to this license on the LicenseServer by using the Management Console of BayesiaLicenseServer. Use this constructor if you use a license server.

Parameters:

stream - the stream of the xbl file containing the network

licenseServerHost - the host of the license server.

licenseServerPort - the port of the license server.

userName - the user name corresponding to an existing access added to the license on the license server. Cannot be null.

password - the passord corresponding to the access added to the license on the license server. Cannot be null.

account - the account corresponding to the license. Cannot be null, but can be set as empty String on dedicated BLS.

inferenceType - one of EXACT_INFERENCE and APPROXIMATE_INFERENCE.

APIInference

public APIInference(java.lang.String fileName,
                    java.lang.String licenseServerHost,
                    int licenseServerPort,
                    java.lang.String userName,
                    java.lang.String password,
                    java.lang.String account,
                    int inferenceType)

Creates a new APIInference with the network stored in the specified file. You must provide the host and the port of the license server. You must provide also the user name and the password of an access added to the license. This access must be associated to this license on the LicenseServer by using the Management Console of BayesiaLicenseServer. Use this constructor if you use a license server.

Parameters:

fileName - the name of the xbl file containing the network

licenseServerHost - the host of the license server.

licenseServerPort - the port of the license server.

userName - the user name corresponding to an existing access added to the license on the license server. Cannot be null.

password - the password corresponding to the access added to the license on the license server. Cannot be null.

account - the account corresponding to the license. Cannot be null, but can be set as empty String on dedicated BLS.

inferenceType - one of EXACT_INFERENCE and APPROXIMATE_INFERENCE.

APIInference

public APIInference(BayesianNetworkTransferHandler networkHandler,
                    java.lang.String licenseKey,
                    int inferenceType)

Creates a new APIInference with the network stored in the specified BayesianNetworkTransferHandler. You must provide a valid license key for inference.

Parameters:

networkHandler - the transfer handler containing the network

licenseKey - the key of the license.

inferenceType - one of EXACT_INFERENCE and APPROXIMATE_INFERENCE.

APIInference

public APIInference(BayesianNetworkTransferHandler networkHandler,
                    java.lang.String licenseServerHost,
                    int licenseServerPort,
                    java.lang.String userName,
                    java.lang.String password,
                    java.lang.String account,
                    int inferenceType)

Creates a new APIInference with the network stored in the specified BayesianNetworkTransferHandler. You must provide the host and the port of the license server. You must provide also the user name and the password of an access added to the license. This access must be associated to this license on the LicenseServer by using the Management Console of BayesiaLicenseServer. Use this constructor if you use a license server.

Parameters:

networkHandler - the transfer handler containing the network.

licenseServerHost - the host of the license server.

licenseServerPort - the port of the license server.

userName - the user name corresponding to an existing access added to the license on the license server. Cannot be null.

password - the passord corresponding to the access added to the license on the license server. Cannot be null.

account - the account corresponding to the license. Cannot be null, but can be set as empty String on dedicated BLS.

inferenceType - one of EXACT_INFERENCE and APPROXIMATE_INFERENCE.

Method Detail

isObservationValidityEnabled

public final boolean isObservationValidityEnabled()

Returns the state of the observation validity checking.

Returns:

true is the observation validity is enabled, false otherwise

setObservationValidityEnabled

public final void setObservationValidityEnabled(boolean b)

Sets the observation validity enabled or not. Enabling observation validity prevent from observing impossible state (its probability is 0). It may cause performance degradation if there are a lot of observations to do.

With this option enabled : observe("aNode", "aValue");

is equal to, with this option disabled : if (getProbability("aNode", "aValue")>0) { observe("aNode", "aValue"); }

When fixed probabilities or fixed mean are involved, only with exact inference, a convergence algorithm is used to reach the target probabilities or target mean. Each time a new observation is done (hard evidence, or other fixed probabilities or fixed mean), the convergence algorithm tries to reach the target probabilities or target mean for each concerned nodes. If it fails, then the current observation method will return false.

Parameters:

b - the new state of the observation validity checking

See Also:

observe(String, String), observe(String, short), observe(String, double), setObservedProbabilities(String, double[]), setObservedMean(String, double, boolean)

getName

public final java.lang.String getName()

Returns the name of the loaded network.

Returns:

the name of the network

getNodeNames

public java.lang.String[] getNodeNames()

Returns an array containing the name of the nodes in the network

Returns:

the node names

getSortedNodeNames

public final java.lang.String[] getSortedNodeNames(APIUtils.NODE_SORTING_METHOD sortingMethod,
                                                   boolean increase)

Return an array containing the name of the nodes in the network sorted according to the APIUtils.NODE_SORTING_METHOD

Parameters:

sortingMethod - the sorting method

increase - true if you want an increasing order, false if you want a decreasing order

Returns:

the sorted node names

getStandardNodeNames

public final java.lang.String[] getStandardNodeNames()

Returns the list of the names of standard chance nodes (neither constraint nor decision nor utility nor function).

Returns:

the standard chance node names

getDiscreteNodeNames

public final java.lang.String[] getDiscreteNodeNames()

Returns the list of the names of simple discrete nodes (neither interval nor constraint nor decision nor utility nor function).

Returns:

the discrete node names

getContinuousNodeNames

public final java.lang.String[] getContinuousNodeNames()

Returns the list of the names of simple continuous nodes (neither discrete nor constraint nor decision nor utility nor function).

Returns:

the continuous node names

getConstraintNodeNames

public final java.lang.String[] getConstraintNodeNames()

Returns the list of the names of constraint nodes.

Returns:

the constraint node names

getDecisionNodeNames

public final java.lang.String[] getDecisionNodeNames()

Returns the list of the names of decision nodes.

Returns:

the decision node names

getUtilityNodeNames

public final java.lang.String[] getUtilityNodeNames()

Returns the list of the names of utility nodes.

Returns:

the utility node names

getFunctionNodeNames

public final java.lang.String[] getFunctionNodeNames()

Returns the list of the names of function nodes.

Returns:

the function node names

containsNode

public final boolean containsNode(java.lang.String nodeName)

Tests if a node with the given name exists in the network

Parameters:

nodeName - the name of the node

Returns:

true if the corresponding node exists and false otherwise

getNodeNumber

public final int getNodeNumber()

Returns the number of nodes in the network

Returns:

the number of nodes

getComment

public final java.lang.String getComment()

Returns the html comment associated to the network.

Returns:

the comment associated to the network in html format

getStringComment

public final java.lang.String getStringComment()

Returns the comment as string associated to the network.

Returns:

the comment associated to the network converted into a simple string

getBackgroundImage

public final ResizableIcon getBackgroundImage()

Gets the image associated to the network.

Returns:

an instance of BufferedImage or null if there is no image

See Also:

ResizableIcon

hasTargetNode

public final boolean hasTargetNode()

Tests if the network has a target node defined

Returns:

true if a target node is defined, false otherwise

getTargetNodeName

public final java.lang.String getTargetNodeName()

Returns the name of the target node of the network.

Returns:

the name of the target node if it exists or null otherwise

getTargetState

public final short getTargetState()

Returns the target state of the target node

Returns:

a short indicating the target state

setTargetNode

public final void setTargetNode(java.lang.String nodeName,
                                short state)

Set the given node as target node with the given target state. If the name of the node is null, the current target node is removed.

Parameters:

nodeName - the name of the node to be set as target or null to remove target node

state - the index of the target state. Ignored when removing target.

hasStandardNodes

public final boolean hasStandardNodes()

Tests if the networks contains standard chance nodes (neither constraint nor decision nor utility nor function).

Returns:

true if there is at least one standard chance node

hasDiscreteNodes

public final boolean hasDiscreteNodes()

Tests if the networks contains simple discrete nodes (neither interval nor constraint nor decision nor utility nor function).

Returns:

true if there is at least one discrete node

hasContinuousNodes

public final boolean hasContinuousNodes()

Tests if the networks contains continuous nodes (neither discrete nor constraint nor decision nor utility nor function).

Returns:

true if there is at least one constraint node

hasConstraintNodes

public final boolean hasConstraintNodes()

Tests if the networks contains constraint nodes.

Returns:

true if there is at least one constraint node

hasDecisionNodes

public final boolean hasDecisionNodes()

Tests if the networks contains decision nodes.

Returns:

true if there is at least one decision node

hasUtilityNodes

public final boolean hasUtilityNodes()

Tests if the networks contains utility nodes.

Returns:

true if there is at least one utility node

hasFunctionNodes

public final boolean hasFunctionNodes()

Tests if the networks contains function nodes.

Returns:

true if there is at least one utility node

getParents

public final java.lang.String[] getParents(java.lang.String nodeName)

Returns the name of the parents of the specified node

Parameters:

nodeName - the name of the node we want the parents

Returns:

an array containing the name of the parents

getChildren

public final java.lang.String[] getChildren(java.lang.String nodeName)

Returns the name of the children of the specified node

Parameters:

nodeName - the name of the node we want the children

Returns:

and array containing the name of the children

hasArcBetween

public final boolean hasArcBetween(java.lang.String nodeName1,
                                   java.lang.String nodeName2)

Tests if there is an arc between the specified nodes

Parameters:

nodeName1 - the name of one of the nodes

nodeName2 - the name of the other node

Returns:

true if there is an arc between the specified nodes, false otherwise

hasTemporalArcBetween

public final boolean hasTemporalArcBetween(java.lang.String nodeName1,
                                           java.lang.String nodeName2)

Tests if there is a temporal arc between the specified chance nodes

Parameters:

nodeName1 - the name of one of the nodes

nodeName2 - the name of the other node

Returns:

true if there is an arc between the specified nodes and this arc is temporal, false otherwise

isParentOf

public final boolean isParentOf(java.lang.String nodeName1,
                                java.lang.String nodeName2)

Tests if there is an arc from nodeName1 to nodeName2

Parameters:

nodeName1 - the name of the supposed parent

nodeName2 - the name of the supposed child

Returns:

true if nodeName1 is parent of nodeName2

isChildOf

public final boolean isChildOf(java.lang.String nodeName1,
                               java.lang.String nodeName2)

Tests if there is an arc from nodeName2 to nodeName1

Parameters:

nodeName1 - the name of the supposed child

nodeName2 - the name of the supposed parent

Returns:

true if nodeName1 is child of nodeName2

getArcOrientationBetween

public final int getArcOrientationBetween(java.lang.String nodeName1,
                                          java.lang.String nodeName2)

Returns the orientation of the arc between nodeName1 and nodeName2. The possible values are : -1 if there is no arc, 0 if there is an arc from nodeName1 to nodeName2 and 1 if there is an arc from nodeName2 to nodeName1

Parameters:

nodeName1 - the name of one of the nodes

nodeName2 - the name of the other node

Returns:

the orientation of the arc between nodeName1 and nodeName2

getNodeLongName

public final java.lang.String getNodeLongName(java.lang.String nodeName)

Return the long name associated to the specified node or null if there is no long name

Parameters:

nodeName - the name of the node we want the long name

Returns:

the long name of the node

getNodeComment

public final java.lang.String getNodeComment(java.lang.String nodeName)

Returns the html comment associated to the specified node

Parameters:

nodeName - the name of the node we want the html comment

Returns:

the html comment of the node

getNodeCommentAsString

public final java.lang.String getNodeCommentAsString(java.lang.String nodeName)

Returns the comment string associated to the specified node

Parameters:

nodeName - the name of the node we want the comment

Returns:

the html comment of the node converted into a simple string

getArcComment

public final java.lang.String getArcComment(java.lang.String nodeName1,
                                            java.lang.String nodeName2)

Returns the html comment associated to the arc between the nodes named nodeName1 and nodeName2.

Parameters:

nodeName1 - the name of the first extremity node

nodeName2 - the name of the second extremity node

Returns:

the comment of the arc in html format

getArcCommentAsString

public final java.lang.String getArcCommentAsString(java.lang.String nodeName1,
                                                    java.lang.String nodeName2)

Returns the comment string associated to the arc between the nodes named nodeName1 and nodeName2.

Parameters:

nodeName1 - the name of the first extremity node

nodeName2 - the name of the second extremity node

Returns:

the comment of the arc converted into a simple string

isInteger

public final boolean isInteger(java.lang.String nodeName)

Tests if all the values of the specified node are integers.

Parameters:

nodeName - the name of the tested node

Returns:

true if the node values are integers, false otherwise

isReal

public final boolean isReal(java.lang.String nodeName)

Tests if all the values of the specified node are reals.

Parameters:

nodeName - the name of the tested node

Returns:

true if the node values are reals, false otherwise

isBoolean

public final boolean isBoolean(java.lang.String nodeName)

Tests if the specified node is boolean, i.e. its values are equivalent to true and false.

Parameters:

nodeName - the name of the tested node

Returns:

true if the is boolean, false otherwise

isInterval

public final boolean isInterval(java.lang.String nodeName)

Tests if the node is described by a list of consecutives intervals.

Parameters:

nodeName - the name of the tested node

Returns:

true if the node is an interval node, false otherwise

isStandard

public final boolean isStandard(java.lang.String nodeName)

Tests if the node is a standard chance node (neither constraint nor decision nor utility nor function).

Parameters:

nodeName - the name of the tested node

Returns:

true if the node is a chance node, false otherwise

isDecision

public final boolean isDecision(java.lang.String nodeName)

Tests if the node is a decision node.

Parameters:

nodeName - the name of the tested node

Returns:

true if the node is a decision node, false otherwise

isUtility

public final boolean isUtility(java.lang.String nodeName)

Tests if the node is a utility node.

Parameters:

nodeName - the name of the tested node

Returns:

true if the node is a utility node, false otherwise

isConstraint

public final boolean isConstraint(java.lang.String nodeName)

Tests if the node is a constraint node.

Parameters:

nodeName - the name of the tested node

Returns:

true if the node is a constraint node, false otherwise

isFunction

public final boolean isFunction(java.lang.String nodeName)

Tests if the node is a function node.

Parameters:

nodeName - the name of the tested node

Returns:

true if the node is a function node, false otherwise

getStateCount

public final int getStateCount(java.lang.String nodeName)

Returns the number of states of the specified node. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

the number of states of the node

hasFilteredState

public final boolean hasFilteredState(java.lang.String nodeName)

Tests if the specified node has a filtered state.

Parameters:

nodeName - the name of the node

Returns:

true if the node has a filtered state, false otherwise

getFilteredState

public final java.lang.String getFilteredState(java.lang.String nodeName)

Returns the name of the filtered state of the specified node or null if the node does not have a filtered state. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

the name of the filtered state if the node has a filtered state or null otherwise

See Also:

getFilteredIndex(String), hasFilteredState(String)

getFilteredIndex

public final short getFilteredIndex(java.lang.String nodeName)

Returns the index of the filtered state of the specified node or -1 if the node does not have a filtered state. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

the index of the filtered state if the node has a filtered state or -1 otherwise

See Also:

getFilteredState(String), hasFilteredState(String)

getStringValues

public final java.lang.String[] getStringValues(java.lang.String nodeName)

Returns an array containing the states of the node as String . It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

an array containing the states of the node.

getIntValues

public final int[] getIntValues(java.lang.String nodeName)

Returns an array containing the states of the node as integers if the node is an integer node. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

an array containing the states of the node as integers.

getRealValues

public final double[] getRealValues(java.lang.String nodeName)

Returns an array containing the states of the node as doubles if all the node's values are real numberss. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

an array containing the states of the node as doubles.

getIntervals

public final double[][] getIntervals(java.lang.String nodeName)

Returns an array containing the minimum and the maximum of each interval of the node as doubles. For each interval, the minimum is at index 0 and the maximum at index 1. It can be used only interval nodes.

Parameters:

nodeName - the name of the node

Returns:

an array containing the minimum and the maximum values of the intervals of the node.

getFormula

public final java.lang.String getFormula(java.lang.String nodeName)

Returns the formula associated to the node as String. If the node doesn't have a formula it return an empty String.

Parameters:

nodeName - the name of the node

Returns:

a String representing the formula of the node

getNodePosition

public final java.awt.geom.Point2D getNodePosition(java.lang.String nodeName)

Returns the position of the center of the node as a point with double precision.

Parameters:

nodeName - the name of the node

Returns:

the position of the node as a point with double coordinates

getNodeColor

public final java.awt.Color getNodeColor(java.lang.String nodeName)

Returns the Color associated to the node or null if there is no associated color.

Parameters:

nodeName - the name of the node

Returns:

an instance of Color or null if no color is associated

getNodeImage

public final ResizableIcon getNodeImage(java.lang.String nodeName)

Gets the image as an instance of ResizableIcon associated to the node or null if there is no associated image.

Parameters:

nodeName - the name of the node

Returns:

an instance of BufferedImage if there is an image or null otherwise

See Also:

ResizableIcon

getNodeCost

public final java.lang.Double getNodeCost(java.lang.String nodeName)

Returns the cost associated to the node or null if there is no cost.

Parameters:

nodeName - the node of the name

Returns:

the cost of the node or null if there is no cost

getNodeFilteredState

public final short getNodeFilteredState(java.lang.String nodeName)

Returns the index of the node's filtered state. If the value equals -1, the node doesn't have any filtered state.

Parameters:

nodeName - the name of the node

Returns:

the index of the filtered state or -1 if there is no filtered state

getNodeReferenceState

public final short getNodeReferenceState(java.lang.String nodeName)

Returns the index of the node's reference state. If the value equals -1, the node doesn't have any reference state.

Parameters:

nodeName - the name of the node

Returns:

the index of the reference state or -1 if there is no reference state

getStateLongNames

public final java.lang.String[] getStateLongNames(java.lang.String nodeName)

Returns an array of String containing the long name for each state of the specified node. A state can have a long name or not. In this last case, the value will be null.

Parameters:

nodeName - the name of the node

Returns:

an array of String containing the state long names

getStateLongNameAt

public final java.lang.String getStateLongNameAt(java.lang.String nodeName,
                                                 int state)

Returns the long names of a given state for a given node. If the state doesn't have a long name, it returns null.

Parameters:

nodeName - the name of the node

state - the index of the state

Returns:

a String representing the long name

getStateValues

public final java.lang.Double[] getStateValues(java.lang.String nodeName)

Returns an array of Double containing the values associated to each state of the given node. If a state has no value associated, the corresponding Double will be null in the array. If no state has an associated value, null is returned.

Parameters:

nodeName - the name of the node

Returns:

an array of Double or null if there is no values associated to any state

getStateValueAt

public final java.lang.Double getStateValueAt(java.lang.String nodeName,
                                              int state)

Returns the value associated to the given state of the given node. If the state has no associated value, null is returned.

Parameters:

nodeName - the name of the node

state - the index of the state we want the value

Returns:

a Double representing the associated value

getCompletedStateValues

public final java.lang.Double[] getCompletedStateValues(java.lang.String nodeName)

Returns an array of Double with a value or null for each state of the node.

• First of all, if the node has values associated to its states, these values are returned.
• Otherwise if the node has integer or real states, they are returned.
• After that, if the node has intervals, the returned array is created by taking the center of each intervals.
• If none of these cases fits, a list with values from 0 to the number of states -1 is returned.

If a state has no associated value, in the first case, or if a state is filtered, the corresponding returned value in the array is null.

Parameters:

nodeName - the name of the node

Returns:

an array of Double representing values of the states. Some of these values can be null

getClasses

public final java.lang.String[] getClasses()

Returns an array containing the name of the classes declared in the network.

Returns:

an array of String representing the list of the classes or null if there is no class in the network

containsClass

public final boolean containsClass(java.lang.String className)

Tests if a class with the given name exists in the network

Parameters:

className - the name of the class

Returns:

true if the corresponding class exists and false otherwise

getNodeClasses

public final java.lang.String[] getNodeClasses(java.lang.String nodeName)

Returns the classes of which the given node is associated.

Parameters:

nodeName - the name of the node

Returns:

an array of String representing the list of the classes or null if there is no class in which the node is involved

nodeContainsClass

public final boolean nodeContainsClass(java.lang.String nodeName,
                                       java.lang.String className)

Tests if a class with the given name exists in the given node

Parameters:

nodeName - the name of the node

className - the name of the class

Returns:

true if the corresponding class exists in the node and false otherwise

getClassNodes

public final java.lang.String[] getClassNodes(java.lang.String className)

Returns an array containing the list of the node belonging to the given class.

Parameters:

className - the name of the class

Returns:

an array of String containing the name of the nodes belonging to the class

isObserved

public final boolean isObserved(java.lang.String nodeName)

Tests if the specified node is observed. It can be a hard evidence, a soft evidence with likelihoods, target probabilities or target mean. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

true if the node is hard observed or a its likelihood, target probability distribution or target mean are set, false otherwise

See Also:

isHardObserved(String), isLikelihoodObserved(String), isProbabilityObserved(String), isMeanObserved(String)

isHardObserved

public final boolean isHardObserved(java.lang.String nodeName)

Returns true if the node has hard evidence set, i.e. a state if observed.

Parameters:

nodeName - the name of the node

Returns:

true if the node is hard observed, false otherwise

See Also:

observe(String, String), observe(String, short), observe(String, double)

isLikelihoodObserved

public final boolean isLikelihoodObserved(java.lang.String nodeName)

Returns true if the node is observed with likelihoods.

Parameters:

nodeName - the name of the node

Returns:

true if the node id observed with likelihoods set

See Also:

setLikelihood(String, short, double), setLikelihood(String, String, double), setLikelihoods(String, double[]), setLikelihoodFromProbabilities(String, double[]), setLikelihoodFromMean(String, double, boolean)

isProbabilityObserved

public final boolean isProbabilityObserved(java.lang.String nodeName)

Returns true if the node is observed with target probabilities.

Parameters:

nodeName - the name of the node

Returns:

true if the node is observed with target probabilities, false otherwise

See Also:

setObservedProbabilities(String, double[])

isMeanObserved

public final boolean isMeanObserved(java.lang.String nodeName)

Returns true if the node is observed with target mean.

Parameters:

nodeName - the name of the node

Returns:

true if the node is observed with target mean, false otherwise

See Also:

setObservedMean(String, double, boolean)

getObservedValue

public final java.lang.String getObservedValue(java.lang.String nodeName)

Returns the observed value of the specified node if the node is hard observed. Returns null if the node is not observed or if its likelihood, probability distribution or mean are set. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

the observed value if the node is hard observed, null otherwise

See Also:

isHardObserved(String), observe(String, String), observe(String, short), observe(String, double)

getObservedIndex

public final short getObservedIndex(java.lang.String nodeName)

Returns the index of the observed state of the specified node if the node is hard observed. Returns -1 if the node is not observed or if its likelihood, probability distribution or mean are set. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

the observed index if the node is hard observed, -1 otherwise

See Also:

isHardObserved(String), observe(String, String), observe(String, short), observe(String, double)

getObservedProbabilities

public final double[] getObservedProbabilities(java.lang.String nodeName)

Returns the target probabilities of the specified node if the node is probability observed. Returns null if the node is hard observed, not observed or if its likelihood or mean are set. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

the observer probability distribution if the node is probability observed, null otherwise

See Also:

isProbabilityObserved(String), setObservedProbabilities(String, double[])

getObservedMean

public final java.lang.Double getObservedMean(java.lang.String nodeName)

Returns the target mean of the specified node if the node is mean observed. Returns null if the node is hard observed, not observed or if its likelihood or probability distribution are set. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

the observed mean if the node is mean observed, null otherwise

See Also:

isMeanObserved(String), setObservedMean(String, double, boolean)

isObservedMeanBinary

public final boolean isObservedMeanBinary(java.lang.String nodeName)

Returns true if the distribution used to compute the mean is binary, false if the distribution is generated by MinXEnt. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

true is the observation mode for the mean is binary or false for MinXEnt

See Also:

isMeanObserved(String), setObservedMean(String, double, boolean), getObservedMean(String)

observe

public final boolean observe(java.lang.String nodeName,
                             java.lang.String value)

Observes a value for a node. Return true if the observation succeed. If isObservationValidityEnabled() returns true, it can return false if the observation is not possible, i.e. the posterior probability of the observed value is 0. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node we want to observe

value - the value to observe

Returns:

true if the observation is possible or if the observation validity is disabled, false otherwise

See Also:

isObservationValidityEnabled(), setObservationValidityEnabled(boolean)

observe

public final boolean observe(java.lang.String nodeName,
                             short valueIndex)

Observes a value through its index for a node. Return true if the observation succeed. If isObservationValidityEnabled() returns true, it can return false if the observation is not possible, i.e. the posterior probability of the observed value is 0. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node we want to observe

valueIndex - the index of the value to observe

Returns:

true if the observation is possible or if the observation validity is disabled, false otherwise

See Also:

isObservationValidityEnabled(), setObservationValidityEnabled(boolean)

observe

public final boolean observe(java.lang.String nodeName,
                             double value)

Observes a double value for an interval node only. Return true if the observation succeed. If isObservationValidityEnabled() returns true, it can return false if the observation is not possible, i.e. the posterior probability of the observed value is 0. It can be used only on interval nodes.

Parameters:

nodeName - the name of the interval node we want to observe

value - the value to observe

Returns:

true if the observation is possible or if the observation validity is disabled, false otherwise

See Also:

getIntervalForValue(java.lang.String, double), isObservationValidityEnabled(), setObservationValidityEnabled(boolean)

getIntervalForValue

public final short getIntervalForValue(java.lang.String nodeName,
                                       double value)

Retrieves the index of the interval corresponding to the specified double value for an continuous node only. Return 0 if the value is less than the minimum of the first interval and (number of interval - 1) if the value is greater than the maximum of the last interval. It can be used only on interval nodes.

Parameters:

nodeName - the name of the interval node we want to find the interval

value - the value

Returns:

the index of the interval corresponding to the specified value

setLikelihood

public final boolean setLikelihood(java.lang.String nodeName,
                                   java.lang.String value,
                                   double likelihood)

Sets the likelihood for a value of a node (soft evidence). The likelihood must be between 0 and 1. Return true if the operation succeed. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

value - the value of the node

likelihood - the likelihood associated to the given value

Returns:

true if the given likelihood is possible, false otherwise

setLikelihood

public final boolean setLikelihood(java.lang.String nodeName,
                                   short valueIndex,
                                   double likelihood)

Sets the likelihood for a value of a node (soft evidence). The likelihood must be between 0 and 1. Return true if the operation succeed. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

valueIndex - the index of the value of the node

likelihood - the likelihood associated to the given index value

Returns:

true if the given likelihood is possible, false otherwise

setLikelihoods

public final boolean setLikelihoods(java.lang.String nodeName,
                                    double[] likelihoods)

Sets the likelihoods for all the values of a node. The likelihoods must be between 0 and 1. Return true if the operation succeed. It can't be used on constraint and utility nodes. As inference must be done in order to compute the final likelihoods, it may take some time to obtain the result.

Parameters:

nodeName - the name of the node

likelihoods - the wanted likelihood distribution

Returns:

true if the given likelihood distribution is possible, false otherwise

setLikelihoodFromProbabilities

public final boolean setLikelihoodFromProbabilities(java.lang.String nodeName,
                                                    double[] probabilities)

Computes the likelihood for all the values of a node in order to have its probabilities equal to the specified ones. The probabilities must be between 0 and 1 and the sum of the probabilities must equal 1. Return true if the operation succeed. It can't be used on constraint and utility nodes. As inference must be done in order to compute the final likelihoods, it may take some time to obtain the result.

Parameters:

nodeName - the name of the node

probabilities - the wanted probability distribution

Returns:

true if the given probability distribution is possible, false otherwise

setLikelihoodFromMean

public final boolean setLikelihoodFromMean(java.lang.String nodeName,
                                           double mean,
                                           boolean binaryDistribution)

Computes the likelihood for all the values of a node in order to have its mean equal to the specified one. Return true if the operation succeed. It can't be used on constraint and utility nodes. As inference must be done in order to compute the final likelihoods, it may take some time to obtain the result.

The mean is computed with the values obtained by getValues(nodeName).

Warning:There is no guarantee that the wanted mean can be obtained exactly.

Parameters:

nodeName - the name of the node

mean - the wanted mean

binaryDistribution - true if the associated distribution is binary, false if the distribution is found by using MinXEnt

Returns:

true if the given mean is possible, false otherwise

setObservedProbabilities

public final boolean setObservedProbabilities(java.lang.String nodeName,
                                              double[] probabilities)

Computes the likelihood for all the values of a node in order to have its probabilities equal to the specified ones. The probabilities must be between 0 and 1 and the sum of the probabilities must equal 1. Return true if the operation succeed. It can't be used on constraint and utility nodes. As inference must be done in order to compute the final likelihoods, it may take some time to obtain the result.

Warning:There is no guarantee that the wanted probability distribution can be obtained exactly.

Parameters:

nodeName - the name of the node

probabilities - the wanted probability distribution

Returns:

true if the given probability distribution is possible, false otherwise

See Also:

isObservationValidityEnabled(), setObservationValidityEnabled(boolean)

setObservedMean

public final boolean setObservedMean(java.lang.String nodeName,
                                     double mean,
                                     boolean binaryDistribution)

Computes the likelihood for all the values of a node in order to have its mean equal to the specified one. Return true if the operation succeed. It can't be used on constraint and utility nodes. As inference must be done in order to compute the final likelihoods, it may take some time to obtain the result.

The mean is computed with the values obtained by getValues(nodeName).

Warning:There is no guarantee that the wanted mean can be obtained exactly.

Parameters:

nodeName - the name of the node

mean - the wanted mean

binaryDistribution - true if the associated distribution is binary, false if the distribution is found by using MinXEnt

Returns:

true if the given mean is possible, false otherwise

See Also:

isObservationValidityEnabled(), setObservationValidityEnabled(boolean)

getLikelihoods

public final double[] getLikelihoods(java.lang.String nodeName)

Retrieves an array containing the likelihoods associated to the values of a node. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

Returns:

an array containing the likelihood for each value of the node

getLikelihood

public final double getLikelihood(java.lang.String nodeName,
                                  java.lang.String value)

Returns the likelihood associated to a value of a node. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node

value - the value of the node

Returns:

the likelihood of the specified value

unobserve

public final void unobserve(java.lang.String nodeName)

Unobserves the specified node. Resets also the likelihoods. It can't be used on constraint and utility nodes.

Parameters:

nodeName - the name of the node to unobserve

unobserveAll

public final void unobserveAll()

Unobserves all the nodes. Resets also the likelihoods.

isTemporal

public final boolean isTemporal()

Tests if the network is temporal.

Returns:

true if the network is temporal, false otherwise.

See Also:

getCurrentTime(), resetTime(), increaseTime(), setTime(int)

getCurrentTime

public final int getCurrentTime()

Returns the current time of the network.

Warning: It must be used only if the network is temporal. Please see isTemporal().

Returns:

the current time of the network

See Also:

isTemporal()

resetTime

public final void resetTime()

Resets the time to 0. This method is equivalent to setTime(0).

Warning: It must be used only if the network is temporal. Please see isTemporal().

See Also:

isTemporal(), getCurrentTime(), setTime(int)

increaseTime

public final void increaseTime()

Performs a step of temporal simulation : from getCurrentTime() to getCurrentTime()+1. This method is equivalent to setTime(getCurrentTime()+1).

Warning: It must be used only if the network is temporal. Please see isTemporal().

See Also:

isTemporal(), getCurrentTime(), setTime(int)

setTime

public final void setTime(int time)

Performs a temporal simulation from the current time to the specified time. If the given time is less than the current time, it will restart the simulation from 0. The parameter time must be superior or equal to 0. If time is 0, the method is equivalent to resetTime(). If time equals getCurrentTime()+1, the method is equivalent to increaseTime().

Warning: It must be used only if the network is temporal. Please see isTemporal().

Parameters:

time - the time to reach.

See Also:

isTemporal(), getCurrentTime(), resetTime(), increaseTime()

setInferenceType

public final void setInferenceType(int type)

Sets the type of inference to use. If the parameter is EXACT_INFERENCE a junction tree algorithm will be used otherwise, if the parameter is APPROXIMATE_INFERENCE a likelihood weighting algorithm is used.

Parameters:

type - the type of inference to be used.

See Also:

getInferenceType()

getInferenceType

public final int getInferenceType()

Returns APPROXIMATE_INFERENCE if the inference type is approximate or EXACT_INFERENCE if the inference type is exact.

Returns:

the inference type used.

See Also:

setInferenceType(int)

setSampleSize

public final void setSampleSize(int sampleSize)

Sets the sample size used by approximate inference. It must be superior or equal to 1 and inferior or equal to 1E+8. By default its value is 1000.

Parameters:

sampleSize - the size of samples used by approximate inference.

See Also:

getSampleSize()

getSampleSize

public final int getSampleSize()

Returnss the sample size used to perform the approximate inference.

Returns:

the sample size of approximate inference.

See Also:

setSampleSize(int)

getJointProbability

public final double getJointProbability()

Return the joint probability of the network according to the evidence set.

Warning:This method is only available for EXACT_INFERENCE.

Returns:

the joint probability of the network

getProbabilities

public final double[] getProbabilities(java.lang.String nodeName)

Return the posterior probabilities associated to the values of the specified node. It can't be used on constraint and utility nodes.

Warning:If isObservationValidityEnabled() returns false and an observation on a node was illegal, the method will return an array with 0 as the probability of each state.

Parameters:

nodeName - the name of the node

Returns:

an array containing the probabilities of the node

getProbability

public final double getProbability(java.lang.String nodeName,
                                   java.lang.String value)

Returns the probability associated to a specific value of a node. It can't be used on constraint and utility nodes.

Warning: If isObservationValidityEnabled() returns false and an observation on a node was illegal, the method will return 0 as the probability of the state.

Parameters:

nodeName - the name of the node

value - the value of the node

Returns:

the posterior probability associated to the node

getUtility

public final double[] getUtility(java.lang.String nodeName)

Returns an array containing the minimum utility, the current utility and the maximum utility of a utility node. it can be used only on a utility node.

Warning:If isObservationValidityEnabled() returns false and an observation on a node was illegal, the method will return the minimum utility as the utility of the node.

Parameters:

nodeName - the name of the utility node

Returns:

an array containing the minimum, current and maximum utilities

getGlobalUtility

public final double[] getGlobalUtility()

Returns an array containing the sum of the minimum utilities, the sum of the current utilities and the sum of the maximum utilities of all utility nodes.

Warning:If isObservationValidityEnabled() returns false and an observation on a node was illegal, the method will return the global minimum utility as global utility.

Returns:

an array containing the global minimum, current and maximum utilities

getQualities

public final double[] getQualities(java.lang.String nodeName)

Returns an array containing the qualities of a decision node. it can be used only on a decision node.

Warning:If isObservationValidityEnabled() returns false and an observation on a node was illegal, the method will return 0 as the qualities of the node.

Parameters:

nodeName - the name of the decision node

Returns:

an array containing the qualities

getMean

public final double getMean(java.lang.String nodeName)

Returns the mean of a node. If the node has values associated to its states, these values are used to compute the mean. Otherwise, if the node has intervals, the middle value of each interval is used. If the node has integer or real states, they are used as is.

Parameters:

nodeName - the name of the node

Returns:

the mean of the node

See Also:

getValues(String), getMean(Double[],double[])

getStandardDeviation

public final double getStandardDeviation(java.lang.String nodeName)

Returns the standard deviation of a node. If the node has values associated to its states, these values are used to compute the standard deviation. Otherwise, if the node has intervals, the middle value of each interval is used. If the node has integer or real states, they are used as is to compute the standard deviation.

Parameters:

nodeName - the name of the node

Returns:

the standard deviation of the node

See Also:

getValues(String), getStandardDeviation(double,Double[],double[])

getValues

public final java.lang.Double[] getValues(java.lang.String nodeName)

Returns the values associated to the states of the specified node. If the node has values associated to its states, these values are returned as is. Otherwise, if the node has intervals, the middle value of each interval is returned. If the node has integer or real states, they are used as values. At least, if the node has nothing to use as values, the index of the state (starting from 0) is used instead.

These values are use to compute the mean of the node

Parameters:

nodeName - the name of the node

Returns:

an array of the associated values

See Also:

getStateValues(String), getStateValueAt(String, int), getMean(Double[],double[]), getStandardDeviation(double,Double[],double[])

getFunctionValue

public final FunctionValue getFunctionValue(java.lang.String nodeName)

Returns the value of a function node as an instance of FunctionValue.

Parameters:

nodeName - the name of the function node

Returns:

the value of the function node

getMean

public static final double getMean(java.lang.Double[] values,
                                   double[] probabilities)

Computes the mean given the values and the probability distribution. Some null values are allowed if there is at least one existing value. If the sum of the probabilities is 0, Double.NaN is returned.

Parameters:

values - an array of Double. Some of them can be null

probabilities - a normalized to 1 probability distribution

Returns:

a double representing the mean computed according to the values and the probabilities

getStandardDeviation

public static final double getStandardDeviation(double mean,
                                                java.lang.Double[] values,
                                                double[] probabilities)

Computes the standard deviation given a mean, the values and the probability distribution. Some null values are allowed if there is at least one existing value. If the mean is Double.NaN, Double.NaN is returned.

Parameters:

mean - the already computed mean

values - an array of Double. Some of them can be null

probabilities - a normalized to 1 probability distribution

Returns:

the standard deviation computed according to the different parameters

getMinXEntProbabilities

public final double[] getMinXEntProbabilities(java.lang.String nodeName,
                                              double[] initialProbabilities,
                                              double targetMean)

Try to find the best probability distribution to obtain the target mean starting from the given initial probabilities, minimizing cross-entropy. The method uses the basic MinXEnt algorithm. The target mean must be "reachable" to obtain a correct probability distribution. If the algorithm cannot converge and find a correct distribution, the initial probabilies are returned.

Parameters:

nodeName - the name of the node

initialProbabilities - the initial probability distribution, normalized to 1

targetMean - the target mean to obtain.

Returns:

the probability distribution corresponding to the target mean and minimizing the cross-entropy with the initial probabilities.

save

public final void save(java.lang.String path)

Saves the created network and its associated junction tree (if the inference type is EXACT_INFERENCE) into the file specified by the given path. This method is useful when you start with a network without junction tree and the junction tree is created on the fly. The newly created junction tree is saved with the network and will be loaded the next time the file is used. The extension of the file must be xbl. The name of the network is now the name of the file.

Parameters:

path - the path to an xbl file

save

public final void save(java.io.OutputStream stream)

Saves the created network and its associated junction tree (if the inference type is EXACT_INFERENCE) into the specified OutputStream. This method is useful when you start with a network without junction tree and the junction tree is created on the fly. The newly created junction tree is saved with the network and will be loaded the next time the stream is used.

Parameters:

stream - the output stream where the network is saved

exportNetwork

public final BayesianNetworkTransferHandler exportNetwork(java.lang.String networkName)

Exports the network and its associated junction tree (if the inference type is EXACT_INFERENCE) with the specified name into a BayesianNetworkTransferHandler in order to used it with the APIInference, APIModeling or APILearningfor example. The name of the network must be terminated by .xbl

Parameters:

networkName - the new name of the network with the xbl extension

Returns:

a handler containing the network and its associated junction tree if presents

close

public final void close()

Method used to close the current instance of APIInference.

WARNING: If you use a license server, this method must be called once you don't need the instance anymore. It allows to release the license on the license server.

Specified by:

close in interface java.io.Closeable

Specified by:

close in interface java.lang.AutoCloseable