edu.cmu.tetrad.bayes.UpdatedBayesIm

All Implemented Interfaces:: BayesIm, Simulator, VariableSource, Im, TetradSerializable, Serializable

public final class UpdatedBayesIm extends Object implements BayesIm

Represents a Bayes IM in which all of the conditional probability tables have been updated to take into account evidence. Updated conditional probability values of variables with respect to comabinations of their parent values are calculated on the fly. Values that do not change due to being d-separated from a variable conditional on its parents are not calculated; rather, these are simply looked up in the underlying Bayes IM and returned.

Version:

$Id: $Id

Author:

josephramsey

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor

Description

UpdatedBayesIm(BayesIm bayesIm)

Constructs Bayes net in which CPT's updated for the given evidence are calculated on the fly.

UpdatedBayesIm(BayesIm bayesIm, Evidence evidence)

Constructs Bayes net in which CPT's updated for the given evidence are calculated on the fly.
Method Summary

Modifier and Type

Method

Description

void

clearRow(int nodeIndex, int rowIndex)

Assigns random probability values to the child values of this row that add to 1.

void

clearTable(int nodeIndex)

Randomizes every row in the table for the given node index.

boolean

equals(Object o)

Returns true iff this Bayes net is equal to the given Bayes net.

BayesPm

getBayesPm()

getBayesPm.

int

getCorrespondingNodeIndex(int nodeIndex, BayesIm otherBayesIm)

Returns the index of the given node in the given BayesIm.

Graph

getDag()

getDag.

Evidence

getEvidence()

Getter for the field evidence.

List<Node>

getMeasuredNodes()

getMeasuredNodes.

Node

getNode(int nodeIndex)

Returns the name of the given node.

Node

getNode(String name)

getNode.

int

getNodeIndex(Node node)

Returns the index of the given node.

int

getNumColumns(int nodeIndex)

Returns the number of columns.

int

getNumNodes()

getNumNodes.

int

getNumParents(int nodeIndex)

Returns the number of parents for the given node.

int

getNumRows(int nodeIndex)

Returns the number of rows.

int

getParent(int nodeIndex, int parentIndex)

Returns the ith parent of the givne node.

int

getParentDim(int nodeIndex, int parentIndex)

Returns the dimension of the given parent for the given node.

int[]

getParentDims(int nodeIndex)

Returns the dimensions of the pararents of the given node.

int[]

getParents(int nodeIndex)

Returns the parents of the given node.

int

getParentValue(int nodeIndex, int rowIndex, int colIndex)

Returns the given parent value.

int[]

getParentValues(int nodeIndex, int rowIndex)

Returns the parents values of the given node.

double

getProbability(int nodeIndex, int rowIndex, int colIndex)

Returns the probability for the given cell in the given CPT.

int

getRowIndex(int nodeIndex, int[] values)

getRowIndex.

List<String>

getVariableNames()

getVariableNames.

List<Node>

getVariables()

getVariables.

boolean

isIncomplete(int nodeIndex)

Returns true iff the given node has a Double.NaN value in it.

boolean

isIncomplete(int nodeIndex, int rowIndex)

Returns true iff the given row in the given node has a Double.NaN value in it.

void

normalizeAll()

normalizeAll.

void

normalizeNode(int nodeIndex)

Normalizes all rows in the table associated with a given node.

void

normalizeRow(int nodeIndex, int rowIndex)

Normalizes the given row.

void

randomizeIncompleteRows(int nodeIndex)

Randomizes any row in the table for the given node index that has a Double.NaN value in it.

void

randomizeRow(int nodeIndex, int rowIndex)

Assigns random probability values to the child values of this row that add to 1.

void

randomizeTable(int nodeIndex)

Randomizes every row in the table for the given node index.

static UpdatedBayesIm

serializableInstance()

Generates a simple exemplar of this class to test serialization.

void

setProbability(int nodeIndex, double[][] probMatrix)

setProbability.

void

setProbability(int nodeIndex, int rowIndex, int colIndex, double value)

Sets the probability for the given node at a given row and column in the table for that node.

DataSet

simulateData(int sampleSize, boolean latentDataSaved)

Simulates a data set with the specified number of rows.

DataSet

simulateData(DataSet dataSet, boolean latentDataSaved)

Simulates data based on the provided data set and saves the latent data if specified.

String

toString()

Prints out the probability table for each variable.

Methods inherited from class java.lang.Object
getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface edu.cmu.tetrad.bayes.BayesIm
getCptMapType

Constructor Details
- UpdatedBayesIm
  
  public UpdatedBayesIm(BayesIm bayesIm)
  
  Constructs Bayes net in which CPT's updated for the given evidence are calculated on the fly.
  
  Parameters:
  
  bayesIm - a BayesIm object
- UpdatedBayesIm
  
  public UpdatedBayesIm(BayesIm bayesIm, Evidence evidence)
  
  Constructs Bayes net in which CPT's updated for the given evidence are calculated on the fly.
  
  Parameters:
  
  bayesIm - a BayesIm object
  
  evidence - a Evidence object
Method Details
- serializableInstance
  
  public static UpdatedBayesIm serializableInstance()
  
  Generates a simple exemplar of this class to test serialization.
  
  Returns:
  
  a UpdatedBayesIm object
- getBayesPm
  
  public BayesPm getBayesPm()
  
  getBayesPm.
  
  Specified by:
  
  getBayesPm in interface BayesIm
  
  Returns:
  
  a BayesPm object
- getDag
  
  public Graph getDag()
  
  getDag.
  
  Specified by:
  
  getDag in interface BayesIm
  
  Returns:
  
  a Graph object
- getNumNodes
  
  public int getNumNodes()
  
  getNumNodes.
  
  Specified by:
  
  getNumNodes in interface BayesIm
  
  Returns:
  
  a int
- getNode
  
  public Node getNode(int nodeIndex)
  
  Returns the name of the given node.
  
  Specified by:
  
  getNode in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node.
  
  Returns:
  
  the node corresponding to the given node index.
- getNode
  
  public Node getNode(String name)
  
  getNode.
  
  Specified by:
  
  getNode in interface BayesIm
  
  Parameters:
  
  name - a String object
  
  Returns:
  
  a Node object
- getNodeIndex
  
  public int getNodeIndex(Node node)
  
  Returns the index of the given node.
  
  Specified by:
  
  getNodeIndex in interface BayesIm
  
  Parameters:
  
  node - the given node.
  
  Returns:
  
  the index for that node, or -1 if the node is not in the BayesIm.
- getNumColumns
  
  public int getNumColumns(int nodeIndex)
  
  Returns the number of columns.
  Specified by:
  
  getNumColumns in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node.
  
  Returns:
  
  the number of columns in the table of the given node N with index 'nodeIndex'--that is, the number of possible values that N can take on. That is, if P(N=v0 | P1=v1, P2=v2, ... Pn=vn) is a conditional probability stored in 'probs', then the maximum number of rows in the table for N is #vals(N).
  
  See Also:
  
  BayesIm.getNumRows(int)
- getNumRows
  
  public int getNumRows(int nodeIndex)
  
  Returns the number of rows.
  Specified by:
  
  getNumRows in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node.
  
  Returns:
  
  the number of rows in the table of the given node, which would be the total number of possible combinations of parent values for a given node. That is, if P(N=v0 | P1=v1, P2=v2, ... Pn=vn) is a conditional probability stored in 'probs', then the maximum number of rows in the table for N is #vals(P1) x #vals(P2) x ... x #vals(Pn).
  
  See Also:
  
  BayesIm.getRowIndex(int, int[])
  
  BayesIm.getNumColumns(int)
- getNumParents
  
  public int getNumParents(int nodeIndex)
  
  Returns the number of parents for the given node.
  
  Specified by:
  
  getNumParents in interface BayesIm
  
  Parameters:
  
  nodeIndex - the given node.
  
  Returns:
  
  the number of parents of the given node.
- getParent
  
  public int getParent(int nodeIndex, int parentIndex)
  
  Returns the ith parent of the givne node.
  
  Specified by:
  
  getParent in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node.
  
  parentIndex - the index of the parent.
  
  Returns:
  
  the given parent of the given node.
- getParentDim
  
  public int getParentDim(int nodeIndex, int parentIndex)
  
  Returns the dimension of the given parent for the given node.
  
  Specified by:
  
  getParentDim in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node.
  
  parentIndex - the index of the parent.
  
  Returns:
  
  the dimension of the given parent for the given node.
- getParentDims
  
  public int[] getParentDims(int nodeIndex)
  
  Returns the dimensions of the pararents of the given node.
  Specified by:
  
  getParentDims in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node.
  
  Returns:
  
  (a defensive copy of) the array representing the dimensionality of each parent of a node, that is, the number of values which that node can take on. The order of entries in this array is the same as the order of entries of nodes returned by getParents() for that node.
  
  See Also:
  
  BayesIm.getParents(int)
- getParents
  
  public int[] getParents(int nodeIndex)
  
  Returns the parents of the given node.
  Specified by:
  
  getParents in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node.
  
  Returns:
  
  (a defensive copy of) the array containing all of the parents of a given node in the order in which they are stored internally.
  
  See Also:
  
  BayesIm.getParentDims(int)
- getParentValues
  
  public int[] getParentValues(int nodeIndex, int rowIndex)
  
  Returns the parents values of the given node.
  Specified by:
  
  getParentValues in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node.
  
  rowIndex - the index of the row in question.
  
  Returns:
  
  an array containing the combination of parent values for a given node and given row in the probability table for that node. To get the combination of parent values from the row number, the row number is represented using a variable-base place value system, where the bases for each place value are the dimensions of the parents in the order in which they are given by getParentDims(). For instance, if the row number (base 10) is 103 and the parent dimension array is [3 5 7], we calculate the first value as 103 / 7 = 14 with a remainder of 5. We then divide 14 / 5 = 2 with a remainder of 4. We then divide 2 / 3 = 0 with a remainder of 2. The variable place value representation is [2 4 5], which is the combination of parent values. This is the inverse function of getRowIndex().
  
  See Also:
  
  BayesIm.getNodeIndex(edu.cmu.tetrad.graph.Node)
  
  BayesIm.getRowIndex(int, int[])
- getParentValue
  
  public int getParentValue(int nodeIndex, int rowIndex, int colIndex)
  
  Returns the given parent value.
  
  Specified by:
  
  getParentValue in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node.
  
  rowIndex - the index of the row in question.
  
  colIndex - the index of the column in question.
  
  Returns:
  
  the value in the probability table for the given node, at the given row and column.
- getProbability
  
  public double getProbability(int nodeIndex, int rowIndex, int colIndex)
  
  Returns the probability for the given cell in the given CPT.
  Calculates the probability for the given node, at the given row and column of the conditional probability table (CPT), updated for the evidence provided in the constuctor.
  Specified by:
  
  getProbability in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node in question.
  
  rowIndex - the row in the table for this for node which represents the combination of parent values in question.
  
  colIndex - the column in the table for this node which represents the value of the node in question.
  
  Returns:
  
  the probability for the given node at the given row and column in the table for that node. To get the node index, use getNodeIndex(). To get the row index, use getRowIndex(). To get the column index, use getCategoryIndex() from the underlying BayesPm(). The value returned will represent a conditional probability of the form P(N=v0 | P1=v1, P2=v2, ... , Pn=vn), where N is the node referenced by nodeIndex, v0 is the value referenced by colIndex, and the combination of parent values indicated is the combination indicated by rowIndex.
  
  See Also:
  
  BayesIm.getNodeIndex(edu.cmu.tetrad.graph.Node)
  
  BayesIm.getRowIndex(int, int[])
- getRowIndex
  
  public int getRowIndex(int nodeIndex, int[] values)
  
  getRowIndex.
  Specified by:
  
  getRowIndex in interface BayesIm
  
  Parameters:
  
  nodeIndex - a int
  
  values - an array of int objects
  
  Returns:
  
  a int
  
  See Also:
  
  BayesIm.getParentValues(int, int)
- normalizeAll
  
  public void normalizeAll()
  
  normalizeAll.
  
  Specified by:
  
  normalizeAll in interface BayesIm
- normalizeNode
  
  public void normalizeNode(int nodeIndex)
  
  Normalizes all rows in the table associated with a given node.
  
  Specified by:
  
  normalizeNode in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node in question.
- normalizeRow
  
  public void normalizeRow(int nodeIndex, int rowIndex)
  
  Normalizes the given row.
  
  Specified by:
  
  normalizeRow in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node in question.
  
  rowIndex - the index of the row in question.
- setProbability
  
  public void setProbability(int nodeIndex, double[][] probMatrix)
  
  setProbability.
  
  Specified by:
  
  setProbability in interface BayesIm
  
  Parameters:
  
  nodeIndex - a int
  
  probMatrix - an array of double objects
- setProbability
  
  public void setProbability(int nodeIndex, int rowIndex, int colIndex, double value)
  
  Sets the probability for the given node at a given row and column in the table for that node. To get the node index, use getNodeIndex(). To get the row index, use getRowIndex(). To get the column index, use getCategoryIndex() from the underlying BayesPm(). The value returned will represent a conditional probability of the form P(N=v0 | P1=v1, P2=v2, ... , Pn=vn), where N is the node referenced by nodeIndex, v0 is the value referenced by colIndex, and the combination of parent values indicated is the combination indicated by rowIndex.
  Specified by:
  
  setProbability in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node in question.
  
  rowIndex - the row in the table for this for node which represents the combination of parent values in question.
  
  colIndex - the column in the table for this node which represents the value of the node in question.
  
  value - the desired probability to be set.
  
  See Also:
  
  BayesIm.getProbability(int, int, int)
- getCorrespondingNodeIndex
  
  public int getCorrespondingNodeIndex(int nodeIndex, BayesIm otherBayesIm)
  
  Returns the index of the given node in the given BayesIm.
  
  Specified by:
  
  getCorrespondingNodeIndex in interface BayesIm
  
  Parameters:
  
  nodeIndex - the index of the node in this BayesIm.
  
  otherBayesIm - the BayesIm in which the node is to be found.
  
  Returns:
  
  the index of the node with the given name in the specified BayesIm.
- clearRow
  
  public void clearRow(int nodeIndex, int rowIndex)
  
  Assigns random probability values to the child values of this row that add to 1.
  
  Specified by:
  
  clearRow in interface BayesIm
  
  Parameters:
  
  nodeIndex - the node for the table that this row belongs to.
  
  rowIndex - the index of the row.
- randomizeRow
  
  public void randomizeRow(int nodeIndex, int rowIndex)
  
  Assigns random probability values to the child values of this row that add to 1.
  
  Specified by:
  
  randomizeRow in interface BayesIm
  
  Parameters:
  
  nodeIndex - the node for the table that this row belongs to.
  
  rowIndex - the index of the row.
- randomizeIncompleteRows
  
  public void randomizeIncompleteRows(int nodeIndex)
  
  Randomizes any row in the table for the given node index that has a Double.NaN value in it.
  
  Specified by:
  
  randomizeIncompleteRows in interface BayesIm
  
  Parameters:
  
  nodeIndex - the node for the table whose incomplete rows are to be randomized.
- randomizeTable
  
  public void randomizeTable(int nodeIndex)
  
  Randomizes every row in the table for the given node index.
  
  Specified by:
  
  randomizeTable in interface BayesIm
  
  Parameters:
  
  nodeIndex - the node for the table to be randomized.
- clearTable
  
  public void clearTable(int nodeIndex)
  
  Randomizes every row in the table for the given node index.
  
  Specified by:
  
  clearTable in interface BayesIm
  
  Parameters:
  
  nodeIndex - the node for the table to be randomized.
- isIncomplete
  
  public boolean isIncomplete(int nodeIndex, int rowIndex)
  
  Returns true iff the given row in the given node has a Double.NaN value in it.
  
  Specified by:
  
  isIncomplete in interface BayesIm
  
  Parameters:
  
  nodeIndex - the node for the table whose incomplete rows are to be checked.
  
  rowIndex - the index of the row in question.
  
  Returns:
  
  true iff one of the values in the given row is Double.NaN.
- isIncomplete
  
  public boolean isIncomplete(int nodeIndex)
  
  Returns true iff the given node has a Double.NaN value in it.
  
  Specified by:
  
  isIncomplete in interface BayesIm
  
  Parameters:
  
  nodeIndex - the node for the table whose incomplete rows are to be checked.
  
  Returns:
  
  true iff any value in the table for the given node is Double.NaN.
- simulateData
  
  public DataSet simulateData(int sampleSize, boolean latentDataSaved)
  
  Simulates a data set with the specified number of rows.
  
  Specified by:
  
  simulateData in interface BayesIm
  
  Specified by:
  
  simulateData in interface Simulator
  
  Parameters:
  
  sampleSize - the number of rows to simulate.
  
  latentDataSaved - if true, latent variables are saved in the data set.
  
  Returns:
  
  the simulated data set.
- simulateData
  
  public DataSet simulateData(DataSet dataSet, boolean latentDataSaved)
  
  Simulates data based on the provided data set and saves the latent data if specified.
  
  Specified by:
  
  simulateData in interface BayesIm
  
  Parameters:
  
  dataSet - the data set to simulate data for
  
  latentDataSaved - a boolean value indicating whether the latent data should be saved or not
  
  Returns:
  
  the simulated data set
- getVariables
  
  public List<Node> getVariables()
  
  getVariables.
  
  Specified by:
  
  getVariables in interface BayesIm
  
  Specified by:
  
  getVariables in interface VariableSource
  
  Returns:
  
  a List object
- getVariableNames
  
  public List<String> getVariableNames()
  
  getVariableNames.
  
  Specified by:
  
  getVariableNames in interface BayesIm
  
  Specified by:
  
  getVariableNames in interface VariableSource
  
  Returns:
  
  a List object
- getMeasuredNodes
  
  public List<Node> getMeasuredNodes()
  
  getMeasuredNodes.
  
  Specified by:
  
  getMeasuredNodes in interface BayesIm
  
  Returns:
  
  a List object
- equals
  
  public boolean equals(Object o)
  
  Returns true iff this Bayes net is equal to the given Bayes net. The sense of equality may vary depending on the type of Bayes net.
  
  Specified by:
  
  equals in interface BayesIm
  
  Overrides:
  
  equals in class Object
  
  Parameters:
  
  o - the Bayes net to be compared to this Bayes net.
  
  Returns:
  
  true iff this bayes net is equal to the given Bayes net. The sense of equality may vary depending on the type of Bayes net.
- toString
  
  public String toString()
  
  Prints out the probability table for each variable.
  
  Specified by:
  
  toString in interface BayesIm
  
  Overrides:
  
  toString in class Object
  
  Returns:
  
  a String object
- getEvidence
  
  public Evidence getEvidence()
  
  Getter for the field evidence.
  
  Returns:
  
  a Evidence object

Class UpdatedBayesIm

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface edu.cmu.tetrad.bayes.BayesIm

Constructor Details

UpdatedBayesIm

UpdatedBayesIm

Method Details

serializableInstance

getBayesPm

getDag

getNumNodes

getNode

getNode

getNodeIndex

getNumColumns

getNumRows

getNumParents

getParent

getParentDim

getParentDims

getParents

getParentValues

getParentValue

getProbability

getRowIndex

normalizeAll

normalizeNode

normalizeRow

setProbability

setProbability

getCorrespondingNodeIndex

clearRow

randomizeRow

randomizeIncompleteRows

randomizeTable

clearTable

isIncomplete

isIncomplete

simulateData

simulateData

getVariables

getVariableNames

getMeasuredNodes

equals

toString

getEvidence