Package edu.pitt.csb.mgm

Class MixedUtils

java.lang.Object

edu.pitt.csb.mgm.MixedUtils

public class MixedUtils
extends Object

Created by ajsedgewick on 7/29/15.

Version:

$Id: $Id

Field Summary

Fields

Modifier and Type	Field	Description
static final String	EdgeStatHeader	Constant EdgeStatHeader="TD\tTU\tFL\tFD\tFU\tFPD\tFPU\tFND\tFNU\"{trunked}

Method Summary

Modifier and Type	Method	Description
static int[][]	allEdgeStats(Graph pT, Graph pE)	allEdgeStats.
static int[][]	allEdgeStats(Graph pT, Graph pE, HashMap<String,String> nodeDists)	allEdgeStats.
static double[]	arrayPermute(double[] a)	arrayPermute.
static int[]	arrayPermute(int[] a)	arrayPermute.
static int[]	colMax(cern.colt.matrix.DoubleMatrix2D m)	return vector of the maximum of each column in m (as ints, i.e.
static DataSet	deepCopy(DataSet ds)	Makes a deep copy of a dataset (Nodes copied as well).
static double[]	evenSplitVector(double w, int L)	evenSplitVector.
static GeneralizedSemIm	GaussianCategoricalIm(GeneralizedSemPm pm)	GaussianCategoricalIm.
static GeneralizedSemIm	GaussianCategoricalIm(GeneralizedSemPm pm, boolean discParamRand)	This method is needed to normalize edge parameters for an Instantiated Mixed Model Generates edge parameters for c-d and d-d edges from a single weight, abs(w), drawn by the normal IM constructor.
static GeneralizedSemPm	GaussianCategoricalPm(Graph trueGraph, String paramTemplate)	GaussianCategoricalPm.
static GeneralizedSemPm	GaussianTrinaryPm(Graph trueGraph, HashMap<String,String> nodeDists, int maxSample, String paramTemplate)	GaussianTrinaryPm.
static double[]	generateMixedEdgeParams(double w, int L)	generateMixedEdgeParams.
static DataSet	getContinousData(DataSet ds)	getContinousData.
static int[]	getContinuousInds(List<Node> nodes)	getContinuousInds.
static int[]	getDiscLevels(DataSet ds)	getDiscLevels.
static DataSet	getDiscreteData(DataSet ds)	getDiscreteData.
static int[]	getDiscreteInds(List<Node> nodes)	getDiscreteInds.
static List<String>	getEdgeParams(Node n1, Node n2, GeneralizedSemPm pm)	getEdgeParams.
static List<String>	getEdgeParams(String s1, String s2, GeneralizedSemPm pm)	getEdgeParams.
static Map<String,Integer>	getNodeDists(Graph g)	getNodeDists.
static cern.colt.matrix.DoubleMatrix2D	graphToMatrix(Graph graph)	graphToMatrix.
static cern.colt.matrix.DoubleMatrix2D	graphToMatrix(Graph graph, double undirectedWeight, double directedWeight)	graphToMatrix.
static IndependenceTest	IndTestFromString(String name, DataSet data, double alpha)	Returns independence tests by name located in edu.cmu.tetrad.search and edu.pitt.csb.mgm also supports shorthand for LRT ("lrt) and t-tests ("tlin" for prefer linear (fastest) or "tlog" for prefer logistic)
static boolean	isColinear(DataSet ds, boolean verbose)	Check each pair of variables to see if correlation is 1.
static DataSet	loadData(String dir, String filename)	loadData.
static DataSet	loadDataSet(String dir, String filename)	loadDataSet.
static DataSet	loadDelim(String dir, String filename)	loadDelim.
static void	main(String[] args)	main.
static DataSet	makeContinuousData(DataSet dsMix)	makeContinuousData.
static DataSet	makeMixedData(DataSet dsCont, Map<String,Integer> nodeDists)	makeMixedData.
static DataSet	makeMixedData(DataSet dsCont, Map<String,String> nodeDists, int numCategories)	makeMixedData.
static Graph	makeMixedGraph(Graph g, Map<String,Integer> m)	makeMixedGraph.
static double	numVals(cern.colt.matrix.DoubleMatrix1D vec)	numVals.
static void	setStartsWith(String sta, String template, GeneralizedSemPm pm)	Set all existing parameters that begins with sta to template and also set template for any new parameters
static cern.colt.matrix.DoubleMatrix2D	skeletonToMatrix(Graph graph)	skeletonToMatrix.
static String	stringFrom2dArray(int[][] arr)	stringFrom2dArray.
static Set<Double>	valSet(cern.colt.matrix.DoubleMatrix1D vec)	valSet.
static double	vecMax(cern.colt.matrix.DoubleMatrix1D vec)	vecMax.

Methods inherited from class java.lang.Object

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

Field Details

EdgeStatHeader

public static final String EdgeStatHeader

Constant EdgeStatHeader="TD\tTU\tFL\tFD\tFU\tFPD\tFPU\tFND\tFNU\"{trunked}

See Also:

• Constant Field Values

Method Details

getDiscreteInds

public static int[] getDiscreteInds(List<Node> nodes)

getDiscreteInds.

Parameters:

nodes - a List object

Returns:

an array of objects

getContinuousInds

public static int[] getContinuousInds(List<Node> nodes)

getContinuousInds.

Parameters:

nodes - a List object

Returns:

an array of objects

makeContinuousData

public static DataSet makeContinuousData(DataSet dsMix)

makeContinuousData.

Parameters:

dsMix - a DataSet object

Returns:

a DataSet object

makeMixedData

public static DataSet makeMixedData(DataSet dsCont,
 Map<String,String> nodeDists,
 int numCategories)

makeMixedData.

Parameters:

dsCont - a DataSet object

nodeDists - a Map object

numCategories - a int

Returns:

a DataSet object

makeMixedData

public static DataSet makeMixedData(DataSet dsCont,
 Map<String,Integer> nodeDists)

makeMixedData.

Parameters:

dsCont - a DataSet object

nodeDists - a Map object

Returns:

a DataSet object

deepCopy

public static DataSet deepCopy(DataSet ds)

Makes a deep copy of a dataset (Nodes copied as well). Useful for paralellization

Parameters:

ds - dataset to be copied

Returns:

a DataSet object

getContinousData

public static DataSet getContinousData(DataSet ds)

getContinousData.

Parameters:

ds - a DataSet object

Returns:

a DataSet object

getDiscreteData

public static DataSet getDiscreteData(DataSet ds)

getDiscreteData.

Parameters:

ds - a DataSet object

Returns:

a DataSet object

getDiscLevels

public static int[] getDiscLevels(DataSet ds)

getDiscLevels.

Parameters:

ds - a DataSet object

Returns:

an array of objects

colMax

public static int[] colMax(cern.colt.matrix.DoubleMatrix2D m)

return vector of the maximum of each column in m (as ints, i.e. for discrete data)

Parameters:

m - a DoubleMatrix2D object

Returns:

an array of objects

vecMax

public static double vecMax(cern.colt.matrix.DoubleMatrix1D vec)

vecMax.

Parameters:

vec - a DoubleMatrix1D object

Returns:

a double

numVals

public static double numVals(cern.colt.matrix.DoubleMatrix1D vec)

numVals.

Parameters:

vec - a DoubleMatrix1D object

Returns:

a double

valSet

public static Set<Double> valSet(cern.colt.matrix.DoubleMatrix1D vec)

valSet.

Parameters:

vec - a DoubleMatrix1D object

Returns:

a Set object

GaussianTrinaryPm

public static GeneralizedSemPm GaussianTrinaryPm(Graph trueGraph,
 HashMap<String,String> nodeDists,
 int maxSample,
 String paramTemplate)
                                          throws IllegalStateException

GaussianTrinaryPm.

Parameters:

trueGraph - a Graph object

nodeDists - a HashMap object

maxSample - a int

paramTemplate - a String object

Returns:

a GeneralizedSemPm object

Throws:

IllegalStateException - if any.

GaussianCategoricalPm

public static GeneralizedSemPm GaussianCategoricalPm(Graph trueGraph,
 String paramTemplate)
                                              throws IllegalStateException

GaussianCategoricalPm.

Parameters:

trueGraph - a Graph object

paramTemplate - a String object

Returns:

a GeneralizedSemPm object

Throws:

IllegalStateException - if any.

setStartsWith

public static void setStartsWith(String sta,
 String template,
 GeneralizedSemPm pm)

Set all existing parameters that begins with sta to template and also set template for any new parameters

Parameters:

sta - a String object

template - a String object

pm - a GeneralizedSemPm object

GaussianCategoricalIm

public static GeneralizedSemIm GaussianCategoricalIm(GeneralizedSemPm pm)

GaussianCategoricalIm.

Parameters:

pm - a GeneralizedSemPm object

Returns:

a GeneralizedSemIm object

GaussianCategoricalIm

public static GeneralizedSemIm GaussianCategoricalIm(GeneralizedSemPm pm,
 boolean discParamRand)

This method is needed to normalize edge parameters for an Instantiated Mixed Model Generates edge parameters for c-d and d-d edges from a single weight, abs(w), drawn by the normal IM constructor. Abs(w) is used for d-d edges.

For deterministic, c-d are evenly spaced between -w and w, and d-d are a matrix with w on the diagonal and -w/(categories-1) in the rest. For random, c-d params are uniformly drawn from 0 to 1 then transformed to have w as max value and sum to 0.

Parameters:

pm - a GeneralizedSemPm object

discParamRand - true for random edge generation behavior, false for deterministic

Returns:

a GeneralizedSemIm object

getEdgeParams

public static List<String> getEdgeParams(String s1,
 String s2,
 GeneralizedSemPm pm)

getEdgeParams.

Parameters:

s1 - a String object

s2 - a String object

pm - a GeneralizedSemPm object

Returns:

a List object

arrayPermute

public static double[] arrayPermute(double[] a)

arrayPermute.

Parameters:

a - an array of objects

Returns:

an array of objects

arrayPermute

public static int[] arrayPermute(int[] a)

arrayPermute.

Parameters:

a - an array of objects

Returns:

an array of objects

evenSplitVector

public static double[] evenSplitVector(double w,
 int L)

evenSplitVector.

Parameters:

w - a double

L - a int

Returns:

an array of objects

getEdgeParams

public static List<String> getEdgeParams(Node n1,
 Node n2,
 GeneralizedSemPm pm)

getEdgeParams.

Parameters:

n1 - a Node object

n2 - a Node object

pm - a GeneralizedSemPm object

Returns:

a List object

generateMixedEdgeParams

public static double[] generateMixedEdgeParams(double w,
 int L)

generateMixedEdgeParams.

Parameters:

w - a double

L - a int

Returns:

an array of objects

allEdgeStats

public static int[][] allEdgeStats(Graph pT,
 Graph pE)

allEdgeStats.

Parameters:

pT - a Graph object

pE - a Graph object

Returns:

an array of objects

allEdgeStats

public static int[][] allEdgeStats(Graph pT,
 Graph pE,
 HashMap<String,String> nodeDists)

allEdgeStats.

Parameters:

pT - a Graph object

pE - a Graph object

nodeDists - a HashMap object

Returns:

an array of objects

makeMixedGraph

public static Graph makeMixedGraph(Graph g,
 Map<String,Integer> m)

makeMixedGraph.

Parameters:

g - a Graph object

m - a Map object

Returns:

a Graph object

stringFrom2dArray

public static String stringFrom2dArray(int[][] arr)

stringFrom2dArray.

Parameters:

arr - an array of objects

Returns:

a String object

loadDataSet

public static DataSet loadDataSet(String dir,
 String filename)
                           throws IOException

loadDataSet.

Parameters:

dir - a String object

filename - a String object

Returns:

a DataSet object

Throws:

IOException - if any.

loadDelim

public static DataSet loadDelim(String dir,
 String filename)
                         throws IOException

loadDelim.

Parameters:

dir - a String object

filename - a String object

Returns:

a DataSet object

Throws:

IOException - if any.

getNodeDists

public static Map<String,Integer> getNodeDists(Graph g)

getNodeDists.

Parameters:

g - a Graph object

Returns:

a Map object

loadData

public static DataSet loadData(String dir,
 String filename)
                        throws IOException

loadData.

Parameters:

dir - a String object

filename - a String object

Returns:

a DataSet object

Throws:

IOException - if any.

isColinear

public static boolean isColinear(DataSet ds,
 boolean verbose)

Check each pair of variables to see if correlation is 1. WARNING: calculates correlation matrix, memory heavy when there are lots of variables

Parameters:

ds - a DataSet object

verbose - a boolean

Returns:

a boolean

graphToMatrix

public static cern.colt.matrix.DoubleMatrix2D graphToMatrix(Graph graph,
 double undirectedWeight,
 double directedWeight)

graphToMatrix.

Parameters:

graph - a Graph object

undirectedWeight - a double

directedWeight - a double

Returns:

a DoubleMatrix2D object

skeletonToMatrix

public static cern.colt.matrix.DoubleMatrix2D skeletonToMatrix(Graph graph)

skeletonToMatrix.

Parameters:

graph - a Graph object

Returns:

a DoubleMatrix2D object

graphToMatrix

public static cern.colt.matrix.DoubleMatrix2D graphToMatrix(Graph graph)

graphToMatrix.

Parameters:

graph - a Graph object

Returns:

a DoubleMatrix2D object

IndTestFromString

public static IndependenceTest IndTestFromString(String name,
 DataSet data,
 double alpha)

Returns independence tests by name located in edu.cmu.tetrad.search and edu.pitt.csb.mgm also supports shorthand for LRT ("lrt) and t-tests ("tlin" for prefer linear (fastest) or "tlog" for prefer logistic)

Parameters:

name - a String object

data - a DataSet object

alpha - a double

Returns:

a IndependenceTest object

main

public static void main(String[] args)

main.

Parameters:

args - an array of String objects