Package edu.cmu.tetrad.bayes
Class RowSummingExactUpdater
java.lang.Object
edu.cmu.tetrad.bayes.RowSummingExactUpdater
- All Implemented Interfaces:
BayesUpdater,ManipulatingBayesUpdater,TetradSerializable,Serializable
Performs updating operations on a BayesIm by summing over cells in the joint probability table for the BayesIm. Quite
flexible and fast if almost all of the variables in the Bayes net are in evidence. Can be excruciatingly slow if
numVars - numVarsInEvidence is more than 15.
- Version:
- $Id: $Id
- Author:
- josephramsey
- See Also:
-
Constructor Summary
ConstructorsConstructorDescriptionRowSummingExactUpdater(BayesIm bayesIm) Constructs a new updater for the given Bayes net.RowSummingExactUpdater(BayesIm bayesIm, Evidence evidence) Constructs a new updater for the given Bayes net. -
Method Summary
Modifier and TypeMethodDescriptiondouble[]calculatePriorMarginals(int nodeIndex) Calculates the prior marginal probabilities of the given node.double[]calculateUpdatedMarginals(int nodeIndex) Calculates the updated marginal probabilities of the given node, given the evidence.The BayesIm that this updater bases its update on.Getter for the fieldevidence.doublegetJointMarginal(int[] variables, int[] values) getJointMarginal.Getter for the fieldmanipulatedBayesIm.getManipulatedGraph.doublegetMarginal(int variable, int value) Returns the marginal probability of the given variable taking the given value, given the evidence.The updated BayesIm.booleanisJointMarginalSupported.static RowSummingExactUpdaterGenerates a simple exemplar of this class to test serialization.voidsetEvidence(Evidence evidence) Sets new evidence for the updater.toString()Prints out the most recent marginal.
-
Constructor Details
-
RowSummingExactUpdater
-
RowSummingExactUpdater
-
-
Method Details
-
serializableInstance
Generates a simple exemplar of this class to test serialization.- Returns:
- a
RowSummingExactUpdaterobject
-
getBayesIm
The BayesIm that this updater bases its update on. This BayesIm is not modified; rather, a new BayesIm is created and updated.- Specified by:
getBayesImin interfaceBayesUpdater- Returns:
- a
BayesImobject
-
getManipulatedBayesIm
Getter for the field
manipulatedBayesIm.- Specified by:
getManipulatedBayesImin interfaceManipulatingBayesUpdater- Returns:
- the updated BayesIm.
-
getManipulatedGraph
getManipulatedGraph.
- Specified by:
getManipulatedGraphin interfaceManipulatingBayesUpdater- Returns:
- a
Graphobject
-
getUpdatedBayesIm
The updated BayesIm. This is a different object from the source BayesIm.- Specified by:
getUpdatedBayesImin interfaceManipulatingBayesUpdater- Returns:
- a
BayesImobject - See Also:
-
getEvidence
Getter for the field
evidence.- Specified by:
getEvidencein interfaceManipulatingBayesUpdater- Returns:
- a defensive copy of the evidence.
-
setEvidence
Sets new evidence for the updater. Once this is called, old updating results should not longer be available.Sets new evidence for the updater. Once this is called, old updating results should not longer be available.
- Specified by:
setEvidencein interfaceBayesUpdater- Specified by:
setEvidencein interfaceManipulatingBayesUpdater- Parameters:
evidence- evidence
-
isJointMarginalSupported
public boolean isJointMarginalSupported()isJointMarginalSupported.
- Specified by:
isJointMarginalSupportedin interfaceBayesUpdater- Returns:
- a boolean
-
getJointMarginal
public double getJointMarginal(int[] variables, int[] values) getJointMarginal.
- Specified by:
getJointMarginalin interfaceBayesUpdater- Parameters:
variables- an array of objectsvalues- an array of objects- Returns:
- a double
-
getMarginal
public double getMarginal(int variable, int value) Returns the marginal probability of the given variable taking the given value, given the evidence.Returns the updated graph. This is the graph in which all probabilities of variables conditional on their parents have been updated.
- Specified by:
getMarginalin interfaceBayesUpdater- Specified by:
getMarginalin interfaceManipulatingBayesUpdater- Parameters:
variable- variable indexvalue- category index- Returns:
- P(variable = value | evidence), where evidence is getEvidence().
-
calculatePriorMarginals
public double[] calculatePriorMarginals(int nodeIndex) Calculates the prior marginal probabilities of the given node.- Specified by:
calculatePriorMarginalsin interfaceBayesUpdater- Parameters:
nodeIndex- node index- Returns:
- P(node = value), where value is the value of the node in the Bayes net.
-
calculateUpdatedMarginals
public double[] calculateUpdatedMarginals(int nodeIndex) Calculates the updated marginal probabilities of the given node, given the evidence.- Specified by:
calculateUpdatedMarginalsin interfaceBayesUpdater- Parameters:
nodeIndex- node index- Returns:
- P(node = value | evidence), where value is the value of the node in the Bayes net.
-
toString
-