Package edu.cmu.tetrad.bayes
Class MlBayesImObs
java.lang.Object
edu.cmu.tetrad.bayes.MlBayesImObs
- All Implemented Interfaces:
BayesIm
,Simulator
,VariableSource
,Im
,TetradSerializable
,Serializable
Stores a table of probabilities for a Bayes net and, together with BayesPm and Dag, provides methods to manipulate
this table. The division of labor is as follows. The Dag is responsible for manipulating the basic graphical
structure of the Bayes net. Dag also stores and manipulates the names of the nodes in the graph; there are no method
in either BayesPm or BayesIm to do this. BayesPm stores and manipulates the *categories* of each node in a DAG,
considered as a variable in a Bayes net. The number of categories for a variable can be changed there as well as the
names for those categories. This class, BayesIm, stores the actual probability tables which are implied by the
structures in the other two classes. The implied parameters take the form of conditional probabilities--e.g.,
P(N=v0|P1=v1, P2=v2, ...), for all nodes and all combinations of their parent categories. The set of all such
probabilities is organized in this class as a three-dimensional table of double values. The first dimension
corresponds to the nodes in the Bayes net. For each such node, the second dimension corresponds to a flat list of
combinations of parent categories for that node. The third dimension corresponds to the list of categories for that
node itself. Two methods allow these values to be set and retrieved:
- getWordRatio(int nodeIndex, int rowIndex, int colIndex); and,
- setProbability(int nodeIndex, int rowIndex, int colIndex, int probability).
- getNodeIndex(Node node).
- getRowIndex(int[] parentVals).
- getParents(int nodeIndex)
- getCategoryIndex(Node node)
Thanks to Pucktada Treeratpituk, Frank Wimberly, and Willie Wheeler for advise and earlier versions.> 0
- Author:
- josephramsey
- See Also:
-
Constructor Summary
ConstructorsConstructorDescriptionMlBayesImObs
(BayesIm bayesIm) MlBayesImObs
(BayesPm bayesPm) Constructs a new BayesIm from the given BayesPm, initializing all values as Double.NaN ("?").MlBayesImObs
(BayesPm bayesPm, int initializationMethod) Constructs a new BayesIm from the given BayesPm, initializing values either as MANUAL or RANDOM.MlBayesImObs
(BayesPm bayesPm, BayesIm oldBayesIm, int initializationMethod) Constructs a new BayesIm from the given BayesPm, initializing values either as MANUAL or RANDOM, but using values from the old BayesIm provided where posssible. -
Method Summary
Modifier and TypeMethodDescriptionvoid
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.void
boolean
Returns true iff this Bayes net is equal to the given Bayes net.Returns the underlying Bayes PM.int
getCorrespondingNodeIndex
(int nodeIndex, BayesIm otherBayesIm) Returns the index of the given node in the given BayesIm.getDag()
$DescriptiongetJPD()
Returns the list of measured variables.getNode
(int nodeIndex) Returns the name of the given node.Returns the name of the given node.int
getNodeIndex
(Node node) Returns the index of the given node.int
getNumColumns
(int nodeIndex) Returns the number of columns.int
Returns the name of the given node.int
getNumParents
(int nodeIndex) Returns the number of parents for the given node.int
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 rowIndex) 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) Returns a row index.int[]
getRowValues
(int rowIndex) Returns the list of variable names.Returns the list of variables.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
Normalizes all rows in the tables associated with each of node in turn.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 MlBayesImObs
Generates a simple exemplar of this class to test serialization.void
setProbability
(int rowIndex, double value) void
setProbability
(int nodeIndex, double[][] probMatrix) Sets the probability for the given node.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.simulateData
(int sampleSize, boolean latentDataSaved) Simulates a sample with the given sample size.simulateData
(DataSet dataSet, boolean latentDataSaved) Overwrites the given dataSet with a new simulated dataSet, to avoid allocating memory.toString()
Prints out the probability table for each variable.
-
Constructor Details
-
MlBayesImObs
Constructs a new BayesIm from the given BayesPm, initializing all values as Double.NaN ("?").- Parameters:
bayesPm
- the given Bayes PM. Carries with it the underlying graph model.- Throws:
IllegalArgumentException
- if the array of nodes provided is not a permutation of the nodes contained in the bayes parametric model provided.
-
MlBayesImObs
Constructs a new BayesIm from the given BayesPm, initializing values either as MANUAL or RANDOM. If initialized manually, all values will be set to Double.NaN ("?") in each row; if initialized randomly, all values will distributed randomly in each row.- Parameters:
bayesPm
- the given Bayes PM. Carries with it the underlying graph model.initializationMethod
- either MANUAL or RANDOM.- Throws:
IllegalArgumentException
- if the array of nodes provided is not a permutation of the nodes contained in the bayes parametric model provided.
-
MlBayesImObs
public MlBayesImObs(BayesPm bayesPm, BayesIm oldBayesIm, int initializationMethod) throws IllegalArgumentException Constructs a new BayesIm from the given BayesPm, initializing values either as MANUAL or RANDOM, but using values from the old BayesIm provided where posssible. If initialized manually, all values that cannot be retrieved from oldBayesIm will be set to Double.NaN ("?") in each such row; if initialized randomly, all values that cannot be retrieved from oldBayesIm will distributed randomly in each such row.- Parameters:
bayesPm
- the given Bayes PM. Carries with it the underlying graph model.oldBayesIm
- an already-constructed BayesIm whose values may be used where possible to initialize this BayesIm. May be null.initializationMethod
- either MANUAL or RANDOM.- Throws:
IllegalArgumentException
- if the array of nodes provided is not a permutation of the nodes contained in the bayes parametric model provided.
-
MlBayesImObs
- Throws:
IllegalArgumentException
-
-
Method Details
-
serializableInstance
Generates a simple exemplar of this class to test serialization. -
getBayesPm
Description copied from interface:BayesIm
Returns the underlying Bayes PM.- Specified by:
getBayesPm
in interfaceBayesIm
- Returns:
- this PM.
-
getDag
Description copied from interface:BayesIm
$Description -
getNumNodes
public int getNumNodes()Description copied from interface:BayesIm
Returns the name of the given node.- Specified by:
getNumNodes
in interfaceBayesIm
- Returns:
- the number of nodes in the model.
-
getNode
Description copied from interface:BayesIm
Returns the name of the given node. -
getNode
Description copied from interface:BayesIm
Returns the name of the given node. -
getNodeIndex
Description copied from interface:BayesIm
Returns the index of the given node.- Specified by:
getNodeIndex
in interfaceBayesIm
- Parameters:
node
- the given node.- Returns:
- the index for that node, or -1 if the node is not in the BayesIm.
-
getVariables
Description copied from interface:BayesIm
Returns the list of variables.- Specified by:
getVariables
in interfaceBayesIm
- Specified by:
getVariables
in interfaceVariableSource
- Returns:
- the list of variable for this Bayes net.
-
getMeasuredNodes
Description copied from interface:BayesIm
Returns the list of measured variables.- Specified by:
getMeasuredNodes
in interfaceBayesIm
- Returns:
- the list of measured variableNodes.
-
getVariableNames
Description copied from interface:BayesIm
Returns the list of variable names.- Specified by:
getVariableNames
in interfaceBayesIm
- Specified by:
getVariableNames
in interfaceVariableSource
- Returns:
- the list of variable names for this Bayes net.
-
getNumColumns
public int getNumColumns(int nodeIndex) Description copied from interface:BayesIm
Returns the number of columns.- Specified by:
getNumColumns
in interfaceBayesIm
- Parameters:
nodeIndex
- the index of the node.- Returns:
- this number.
- See Also:
-
getNumRows
public int getNumRows(int nodeIndex) Description copied from interface:BayesIm
Returns the number of rows.- Specified by:
getNumRows
in interfaceBayesIm
- Parameters:
nodeIndex
- the index of the node.- Returns:
- this number.
- See Also:
-
getNumParents
public int getNumParents(int nodeIndex) Description copied from interface:BayesIm
Returns the number of parents for the given node.- Specified by:
getNumParents
in interfaceBayesIm
- Parameters:
nodeIndex
- the given node.- Returns:
- the number of parents for this node.
-
getParent
public int getParent(int nodeIndex, int parentIndex) Description copied from interface:BayesIm
Returns the ith parent of the givne node. -
getParentDim
public int getParentDim(int nodeIndex, int parentIndex) Description copied from interface:BayesIm
Returns the dimension of the given parent for the given node.- Specified by:
getParentDim
in interfaceBayesIm
- 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) Description copied from interface:BayesIm
Returns the dimensions of the pararents of the given node.- Specified by:
getParentDims
in interfaceBayesIm
- Parameters:
nodeIndex
- the index of the node.- Returns:
- this array of parent dimensions.
- See Also:
-
getParents
public int[] getParents(int nodeIndex) Description copied from interface:BayesIm
Returns the parents of the given node.- Specified by:
getParents
in interfaceBayesIm
- 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:
-
getParentValues
public int[] getParentValues(int nodeIndex, int rowIndex) Description copied from interface:BayesIm
Returns the parents values of the given node.- Specified by:
getParentValues
in interfaceBayesIm
- Parameters:
nodeIndex
- the index of the node.rowIndex
- the index of the row in question.- Returns:
- the array representing the combination of parent values for this row.
- See Also:
-
getParentValue
public int getParentValue(int nodeIndex, int rowIndex, int colIndex) Description copied from interface:BayesIm
Returns the given parent value.- Specified by:
getParentValue
in interfaceBayesIm
- 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) Description copied from interface:BayesIm
Returns the probability for the given cell in the given CPT.- Specified by:
getProbability
in interfaceBayesIm
- 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 stored for this parameter.
- See Also:
-
getRowIndex
public int getRowIndex(int nodeIndex, int[] values) Description copied from interface:BayesIm
Returns a row index.- Specified by:
getRowIndex
in interfaceBayesIm
- Parameters:
nodeIndex
- the index of the node in question.values
- the combination of parent values in question.- Returns:
- the row in the table for the given node and combination of parent values.
- See Also:
-
normalizeAll
public void normalizeAll()Normalizes all rows in the tables associated with each of node in turn.- Specified by:
normalizeAll
in interfaceBayesIm
-
normalizeNode
public void normalizeNode(int nodeIndex) Normalizes all rows in the table associated with a given node.- Specified by:
normalizeNode
in interfaceBayesIm
- 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 interfaceBayesIm
- 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) 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 interfaceBayesIm
- 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) 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 interfaceBayesIm
- 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
Description copied from interface:BayesIm
Returns the index of the given node in the given BayesIm.- Specified by:
getCorrespondingNodeIndex
in interfaceBayesIm
- 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. -
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 interfaceBayesIm
- 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 interfaceBayesIm
- 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 interfaceBayesIm
- 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 interfaceBayesIm
- Parameters:
nodeIndex
- the node for the table to be randomized.
-
isIncomplete
public boolean isIncomplete(int nodeIndex, int rowIndex) Description copied from interface:BayesIm
Returns true iff the given row in the given node has a Double.NaN value in it.- Specified by:
isIncomplete
in interfaceBayesIm
- 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) Description copied from interface:BayesIm
Returns true iff the given node has a Double.NaN value in it.- Specified by:
isIncomplete
in interfaceBayesIm
- 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
Simulates a sample with the given sample size.- Specified by:
simulateData
in interfaceBayesIm
- Specified by:
simulateData
in interfaceSimulator
- Parameters:
sampleSize
- the sample size.latentDataSaved
- true iff the latent data is to be saved.- Returns:
- the simulated sample as a DataSet.
-
simulateData
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 interfaceBayesIm
- Parameters:
dataSet
- the dataSet to be overwritten.latentDataSaved
- true iff the latent data is to be saved.- Returns:
- the simulated sample as a DataSet.
-
equals
Description copied from interface:BayesIm
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
Prints out the probability table for each variable. -
getBayesImObs
-
getJPD
-
getNumRows
public int getNumRows() -
getRowValues
public int[] getRowValues(int rowIndex) -
getProbability
public double getProbability(int rowIndex) -
setProbability
public void setProbability(int rowIndex, double value) -
createRandomCellTable
public void createRandomCellTable()
-