Package com.actelion.research.calc

Class MatrixFunctions

java.lang.Object

com.actelion.research.calc.MatrixFunctions

public class MatrixFunctions
extends java.lang.Object

Title: MatrixFunctions

Description: Matrix operations for which a direct access to the matrix member variables is not necessary

References http://www.ini.uzh.ch/~fred/java/Matrix.java https://introcs.cs.princeton.edu/java/95linear/Cholesky.java.html

Copyright: Actelion Ltd., Inc. All Rights Reserved This software is the proprietary information of Actelion Pharmaceuticals, Ltd. Use is subject to license terms.

Version:

1.0 20.11.2003 MvK: Start implementation 10.06.2004 MvK read matrix.

Author:

Modest von Korff

Constructor Summary

Constructors

Constructor	Description
MatrixFunctions()

Method Summary

Modifier and Type	Method	Description
static Matrix	appendCols(Matrix ma0, Matrix ma1)
static Matrix	appendRows(Matrix ma0, Matrix ma1)
static IntegerDouble	calculateMaxSimilarity(Matrix X, double[] arr)
static IntegerDouble[]	calculateMaxSimilarity(Matrix X, double[] arr, int nMostSimilar)
static double[]	calculateMaxSimilarity(Matrix XTrain, Matrix Xtest)
static Matrix	calculateSimilarityMatrixRowWise(Matrix X1, Matrix X2)
static Matrix	cholesky(Matrix A)
static void	columnIntoDoubleArray(Matrix A, int col, DoubleArray da)
static Matrix	convert2Binary(Matrix A, double thresh)
static int	countFieldsBiggerThan(Matrix ma, int row, double thresh)
static Matrix	countFieldsBiggerThanThreshColWise(Matrix ma, double thresh)
static int	countFieldsBiggerThanThreshColWise(Matrix ma, int col, double thresh)
static Matrix	create(java.util.List<double[]> li)	List is already used as a constructor for Matrix.
static java.util.List<IdentifiedObject<double[]>>	createIdentifiedObject(Matrix A)
static boolean	equals(double d1, double d2)
static double	getCorrPearson(Matrix A, int col1, int col2)
static double	getCorrPearson(Matrix A, Matrix B)
static double	getCorrSpearman(Matrix A, Matrix B)
static double	getCovariance(Matrix A, Matrix B)
static double	getCovarianceCentered(Matrix A, Matrix B)
static Matrix	getDistanceMatrix(java.util.List<java.awt.Point> li)
static Matrix	getDistanceMatrixTanimotoInv(Matrix ma1, Matrix ma2)	Calculates the inverse Tanimoto coefficient from row wise comparison of the two input matrices.
static double	getDistanceTanimotoInv(Matrix ma1, int row1, Matrix ma2, int row2)
static double	getDistTanimotoInvReduced(Matrix ma1, int row1, Matrix ma2, int row2)	Only fields are considered which are not nut 0 in both or in one of the rows we from where the distance is calculated.
static Matrix	getDistTanimotoInvReduced(Matrix ma1, Matrix ma2)
static java.util.List<java.awt.Point>	getIndicesUniqueMaxColumnWise(Matrix maIn)
static java.util.List<java.awt.Point>	getIndicesUniqueMaxRowWise(Matrix maIn)
static Matrix	getKMeanClusters(Matrix ma, int k)	03.10.04 MvK
static java.util.List<java.awt.Point>	getMooreNeighborhood(java.awt.Point p, int r, Matrix ma)
static java.util.List<java.awt.Point>	getMooreNeighborhood(java.awt.Point p, Matrix ma)	A square-shaped neighborhood that can be used to define a set of cells surrounding a given point.
static IntVec	getNonZeroCols(Matrix X)
static java.util.List<java.awt.Point>	getPoints(Matrix ma)
static Matrix	getRandomMatrix(int rows, int cols)	generates a matrix with double values between 0 (inclusive) and 1 (exclusive).
static Matrix	getRowMinUnique(Matrix ma)
static Matrix	getScaled(Matrix ma)	Centers and divides by standard deviation.
static Matrix	getScaledByFactor(Matrix ma, double fac)
static double	getSumSquaredDiff(Matrix ma1, int row1, Matrix ma2, int row2)
static double	getTotalSumSquaredDiffRowWise(Matrix ma1, Matrix ma2)
static double[][]	id(int n)	Returns a (n x n) identity matrix.
static Matrix	inv(Matrix A)	Returns the inverse of a matrix.
static boolean	isEqualCol(Matrix A, int colA, Matrix B, int colB, double thresh)
static boolean	isSquare(Matrix A)
static boolean	isSymmetric(Matrix A)
static Matrix	read(java.io.File fiMatrix)
static Matrix	read(java.io.File fiMatrix, boolean skipFirstLine)
static Matrix	read(java.io.InputStream is)
static Matrix	read(java.io.InputStream is, boolean skipFirstLine)
static Matrix	read(java.lang.String s)
static Matrix	readAsLineBase64Encoded(java.lang.String s)
static Matrix	readCSV(java.io.File fi)
static Matrix	rnorm(int n, double mean, double sd)
static Matrix[]	split(Matrix A, int row)	Splits the matrix row wise into two matrices.
static Matrix[]	splitCol(Matrix A, int col)
static double[]	upperTriangle(Matrix maQuadratic)
static void	vecvec2Matrix(java.util.Vector<java.util.Vector<java.lang.Double>> vecvec, Matrix ma)	Converts a vector of vectors into doubles, each vector results in a row in the matrix.
static void	writeQuadraticSymmetricMatrixPairwise(Matrix ma, java.io.File fiTxt)

Methods inherited from class java.lang.Object

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

Constructor Detail

MatrixFunctions

public MatrixFunctions()

Method Detail

convert2Binary

public static Matrix convert2Binary(Matrix A,
                                    double thresh)

split

public static Matrix[] split(Matrix A,
                             int row)

Splits the matrix row wise into two matrices.

Parameters:

A -

row -

Returns:

splitCol

public static Matrix[] splitCol(Matrix A,
                                int col)

isEqualCol

public static boolean isEqualCol(Matrix A,
                                 int colA,
                                 Matrix B,
                                 int colB,
                                 double thresh)

equals

public static boolean equals(double d1,
                             double d2)

id

public static double[][] id(int n)

Returns a (n x n) identity matrix. (The elements on the diagonal have value 1.0, all others are set to 0.0).

Parameters:

n - the size of the matrix

Returns:

the identity matrix

inv

public static Matrix inv(Matrix A)

Returns the inverse of a matrix. The method uses a LU decomposition with pivot. There is no check on the size (is it a square matrix) or the rank (is it inversible, ie det doesn't equal 0).

Parameters:

A -

Returns:

A^(-1)

isSymmetric

public static boolean isSymmetric(Matrix A)

isSquare

public static boolean isSquare(Matrix A)

cholesky

public static Matrix cholesky(Matrix A)

Parameters:

A -

Returns:

Cholesky factor L of psd matrix A = L L^T

calculateSimilarityMatrixRowWise

public static Matrix calculateSimilarityMatrixRowWise(Matrix X1,
                                                      Matrix X2)

calculateMaxSimilarity

public static double[] calculateMaxSimilarity(Matrix XTrain,
                                              Matrix Xtest)

calculateMaxSimilarity

public static IntegerDouble[] calculateMaxSimilarity(Matrix X,
                                                     double[] arr,
                                                     int nMostSimilar)

calculateMaxSimilarity

public static IntegerDouble calculateMaxSimilarity(Matrix X,
                                                   double[] arr)

upperTriangle

public static double[] upperTriangle(Matrix maQuadratic)

Parameters:

maQuadratic -

Returns:

upper triangle from a quadratic matrix as an array.

appendRows

public static Matrix appendRows(Matrix ma0,
                                Matrix ma1)

appendCols

public static Matrix appendCols(Matrix ma0,
                                Matrix ma1)

create

public static Matrix create(java.util.List<double[]> li)

List is already used as a constructor for Matrix. So we have to place this method here.

Parameters:

li -

Returns:

countFieldsBiggerThan

public static int countFieldsBiggerThan(Matrix ma,
                                        int row,
                                        double thresh)

countFieldsBiggerThanThreshColWise

public static int countFieldsBiggerThanThreshColWise(Matrix ma,
                                                     int col,
                                                     double thresh)

countFieldsBiggerThanThreshColWise

public static Matrix countFieldsBiggerThanThreshColWise(Matrix ma,
                                                        double thresh)

getDistanceMatrixTanimotoInv

public static Matrix getDistanceMatrixTanimotoInv(Matrix ma1,
                                                  Matrix ma2)

Calculates the inverse Tanimoto coefficient from row wise comparison of the two input matrices.

Parameters:

ma1 -

ma2 -

Returns:

complete distance matrix calculated between all rows from the two input matrices.

getDistanceMatrix

public static Matrix getDistanceMatrix(java.util.List<java.awt.Point> li)

getDistTanimotoInvReduced

public static Matrix getDistTanimotoInvReduced(Matrix ma1,
                                               Matrix ma2)

getDistanceTanimotoInv

public static double getDistanceTanimotoInv(Matrix ma1,
                                            int row1,
                                            Matrix ma2,
                                            int row2)

Parameters:

ma1 - Matrix

row1 - row

ma2 - Matrix

row2 - row

Returns:

maximum distance = 0, minimum distance = 1

getSumSquaredDiff

public static double getSumSquaredDiff(Matrix ma1,
                                       int row1,
                                       Matrix ma2,
                                       int row2)

getTotalSumSquaredDiffRowWise

public static double getTotalSumSquaredDiffRowWise(Matrix ma1,
                                                   Matrix ma2)

getDistTanimotoInvReduced

public static double getDistTanimotoInvReduced(Matrix ma1,
                                               int row1,
                                               Matrix ma2,
                                               int row2)

Only fields are considered which are not nut 0 in both or in one of the rows we from where the distance is calculated.

Parameters:

ma1 - Matrix

row1 - row

ma2 - Matrix

row2 - row

Returns:

maximum distance = 0, minimum distance = 1

getMooreNeighborhood

public static java.util.List<java.awt.Point> getMooreNeighborhood(java.awt.Point p,
                                                                  Matrix ma)

A square-shaped neighborhood that can be used to define a set of cells surrounding a given point.

Parameters:

p -

ma -

Returns:

getMooreNeighborhood

public static java.util.List<java.awt.Point> getMooreNeighborhood(java.awt.Point p,
                                                                  int r,
                                                                  Matrix ma)

getRowMinUnique

public static Matrix getRowMinUnique(Matrix ma)

Parameters:

ma - Matrix with ma.rows and 1 col. Containing the min value from each row.

Returns:

getPoints

public static java.util.List<java.awt.Point> getPoints(Matrix ma)

Parameters:

ma -

Returns:

list with indices Point(row,col) for values>0.

getIndicesUniqueMaxRowWise

public static java.util.List<java.awt.Point> getIndicesUniqueMaxRowWise(Matrix maIn)

getIndicesUniqueMaxColumnWise

public static java.util.List<java.awt.Point> getIndicesUniqueMaxColumnWise(Matrix maIn)

getScaledByFactor

public static Matrix getScaledByFactor(Matrix ma,
                                       double fac)

getScaled

public static Matrix getScaled(Matrix ma)

Centers and divides by standard deviation.

Parameters:

ma -

Returns:

getKMeanClusters

public static Matrix getKMeanClusters(Matrix ma,
                                      int k)

03.10.04 MvK

Parameters:

ma - matrix with objects in rows

k - number of desired cluster

Returns:

Matrix of cluster centers, k rows and cols equal ma.cols.

getCorrPearson

public static final double getCorrPearson(Matrix A,
                                          Matrix B)

getCorrSpearman

public static final double getCorrSpearman(Matrix A,
                                           Matrix B)

getCorrPearson

public static double getCorrPearson(Matrix A,
                                    int col1,
                                    int col2)

getCovariance

public static double getCovariance(Matrix A,
                                   Matrix B)

getCovarianceCentered

public static double getCovarianceCentered(Matrix A,
                                           Matrix B)

getRandomMatrix

public static Matrix getRandomMatrix(int rows,
                                     int cols)

generates a matrix with double values between 0 (inclusive) and 1 (exclusive).

Parameters:

rows - rows

cols - columns

Returns:

matrix

rnorm

public static Matrix rnorm(int n,
                           double mean,
                           double sd)

Parameters:

n -

mean -

sd -

Returns:

random one column matrix with given mean and standard deviation.

getNonZeroCols

public static IntVec getNonZeroCols(Matrix X)

Parameters:

X -

Returns:

bit wise.

vecvec2Matrix

public static void vecvec2Matrix(java.util.Vector<java.util.Vector<java.lang.Double>> vecvec,
                                 Matrix ma)

Converts a vector of vectors into doubles, each vector results in a row in the matrix. All vectors have to be of equal length or a runtime exception is thrown.

Parameters:

vecvec - vector on vectors, has to be converted into doubles

ma - resulting matrix

readCSV

public static Matrix readCSV(java.io.File fi)
                      throws java.io.IOException

Throws:

java.io.IOException

read

public static Matrix read(java.io.File fiMatrix)
                   throws java.io.IOException

Throws:

java.io.IOException

read

public static Matrix read(java.io.File fiMatrix,
                          boolean skipFirstLine)
                   throws java.io.IOException

Throws:

java.io.IOException

read

public static Matrix read(java.lang.String s)
                   throws java.io.IOException

Throws:

java.io.IOException

readAsLineBase64Encoded

public static Matrix readAsLineBase64Encoded(java.lang.String s)
                                      throws java.io.IOException

Throws:

java.io.IOException

read

public static Matrix read(java.io.InputStream is)

read

public static Matrix read(java.io.InputStream is,
                          boolean skipFirstLine)

writeQuadraticSymmetricMatrixPairwise

public static void writeQuadraticSymmetricMatrixPairwise(Matrix ma,
                                                         java.io.File fiTxt)
                                                  throws java.io.IOException

Throws:

java.io.IOException

columnIntoDoubleArray

public static void columnIntoDoubleArray(Matrix A,
                                         int col,
                                         DoubleArray da)

createIdentifiedObject

public static java.util.List<IdentifiedObject<double[]>> createIdentifiedObject(Matrix A)