Package edu.cmu.tetrad.bayes

Class UpdatedBayesIm

java.lang.Object
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.
Author:
Joseph Ramsey
See Also:

  • Constructor Details

    • UpdatedBayesIm

      public UpdatedBayesIm(BayesIm bayesIm)
      Constructs Bayes net in which CPT's updated for the given evidence are calculated on the fly.

    • UpdatedBayesIm

      public UpdatedBayesIm(BayesIm bayesIm, Evidence evidence)
      Constructs Bayes net in which CPT's updated for the given evidence are calculated on the fly.

  • Method Details

    • serializableInstance

      public static UpdatedBayesIm serializableInstance()
      Generates a simple exemplar of this class to test serialization.

    • getBayesPm

      public BayesPm getBayesPm()
      Specified by:
      getBayesPm in interface BayesIm
      Returns:
      the underlying Bayes PM.

    • getDag

      public Graph getDag()
      Specified by:
      getDag in interface BayesIm
      Returns:
      the underlying DAG.

    • getNumNodes

      public int getNumNodes()
      Specified by:
      getNumNodes in interface BayesIm
      Returns:
      the number of nodes in the model.

    • getNode

      public Node getNode(int nodeIndex)
      Specified by:
      getNode in interface BayesIm
      Returns:
      the node corresponding to the given node index.

    • getNode

      public Node getNode(String name)
      Specified by:
      getNode in interface BayesIm
      Parameters:
      name - the name of the node.
      Returns:
      the node with the given name in the associated graph.

    • getNodeIndex

      public int getNodeIndex(Node 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)
      Specified by:
      getNumColumns in interface BayesIm
      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:

    • getNumRows

      public int getNumRows(int nodeIndex)
      Specified by:
      getNumRows in interface BayesIm
      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:

    • getNumParents

      public int getNumParents(int nodeIndex)
      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)
      Specified by:
      getParent in interface BayesIm
      Returns:
      the given parent of the given node.

    • getParentDim

      public int getParentDim(int nodeIndex, int parentIndex)
      Specified by:
      getParentDim in interface BayesIm
      Returns:
      the dimension of the given parent for the given node.

    • getParentDims

      public int[] getParentDims(int nodeIndex)
      Specified by:
      getParentDims in interface BayesIm
      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:

    • getParents

      public int[] getParents(int nodeIndex)
      Specified by:
      getParents in interface BayesIm
      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:

    • getParentValues

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

    • getParentValue

      public int getParentValue(int nodeIndex, int rowIndex, int colIndex)
      Specified by:
      getParentValue in interface BayesIm
      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)
      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:

    • getRowIndex

      public int getRowIndex(int nodeIndex, int[] values)
      Specified by:
      getRowIndex in interface BayesIm
      Returns:
      the row in the table at which the given combination of parent values is represented for the given node. The row is calculated as a variable-base place-value number. For instance, if the array of parent dimensions is [3, 5, 7] and the parent value combination is [2, 4, 5], then the row number is (7 * (5 * (3 * 0 + 2) + 4)) + 5 = 103. This is the inverse function to getVariableValues().

      Note: If the node has n values, the length of 'values' must be >= the number of parents. Only the first n values are used.

      See Also:

    • normalizeAll

      public void normalizeAll()
      Description copied from interface: BayesIm
      Normalizes all rows in the tables associated with each of node in turn.
      Specified by:
      normalizeAll in interface BayesIm

    • normalizeNode

      public void normalizeNode(int nodeIndex)
      Description copied from interface: BayesIm
      Normalizes all rows in the table associated with a given node.
      Specified by:
      normalizeNode in interface BayesIm

    • normalizeRow

      public void normalizeRow(int nodeIndex, int rowIndex)
      Description copied from interface: BayesIm
      Normalizes the given row.
      Specified by:
      normalizeRow in interface BayesIm

    • setProbability

      public void setProbability(int nodeIndex, double[][] probMatrix)
      Description copied from interface: BayesIm
      Sets the probability for the given node. The matrix row represent row index, the row in the table for this for node which represents the combination of parent values in question. of the CPT. The matrix column represent column index, the column in the table for this node which represents the value of the node in question.
      Specified by:
      setProbability in interface BayesIm
      Parameters:
      nodeIndex - the index of the node in question.
      probMatrix - a matrix containing probabilities of a node along with its parents

    • setProbability

      public void setProbability(int nodeIndex, int rowIndex, int colIndex, double value)
      Description copied from interface: BayesIm
      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:

    • getCorrespondingNodeIndex

      public int getCorrespondingNodeIndex(int nodeIndex, BayesIm otherBayesIm)
      Specified by:
      getCorrespondingNodeIndex in interface BayesIm
      Returns:
      the index of the node with the given name in the specified BayesIm.

    • clearRow

      public void clearRow(int nodeIndex, int rowIndex)
      Description copied from interface: BayesIm
      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)
      Description copied from interface: BayesIm
      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)
      Description copied from interface: BayesIm
      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)
      Description copied from interface: BayesIm
      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)
      Description copied from interface: BayesIm
      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)
      Specified by:
      isIncomplete in interface BayesIm
      Returns:
      true iff one of the values in the given row is Double.NaN.

    • isIncomplete

      public boolean isIncomplete(int nodeIndex)
      Specified by:
      isIncomplete in interface BayesIm
      Returns:
      true iff any value in the table for the given node is Double.NaN.

    • simulateData

      public DataSet simulateData(int sampleSize, boolean latentDataSaved)
      Description copied from interface: BayesIm
      Simulates a sample with the given sample size.
      Specified by:
      simulateData in interface BayesIm
      Specified by:
      simulateData in interface Simulator
      Parameters:
      sampleSize - the sample size.
      Returns:
      the simulated sample as a DataSet.

    • simulateData

      public DataSet simulateData(DataSet dataSet, boolean latentDataSaved)
      Description copied from interface: BayesIm
      Overwrites the given dataSet with a new simulated dataSet, to avoid allocating memory. The given dataSet must have the necessary number of columns.
      Specified by:
      simulateData in interface BayesIm
      Returns:
      the simulated sample as a DataSet.

    • getVariables

      public List<Node> getVariables()
      Specified by:
      getVariables in interface BayesIm
      Specified by:
      getVariables in interface VariableSource
      Returns:
      the list of variable for this Bayes net.

    • getVariableNames

      public List<String> getVariableNames()
      Specified by:
      getVariableNames in interface BayesIm
      Specified by:
      getVariableNames in interface VariableSource
      Returns:
      the list of variable names for this Bayes net.

    • getMeasuredNodes

      public List<Node> getMeasuredNodes()
      Specified by:
      getMeasuredNodes in interface BayesIm
      Returns:
      the list of measured variableNodes.

    • equals

      public boolean equals(Object o)
      Specified by:
      equals in interface BayesIm
      Overrides:
      equals in class Object
      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 representation for this Bayes net.

    • getEvidence

      public Evidence getEvidence()