org.openimaj.math.matrix

Class CFMatrixUtils

java.lang.Object

org.openimaj.math.matrix.CFMatrixUtils

public class CFMatrixUtils
extends Object

Utility methods for dealing with the cognitive foundry Matrix.

Author:

Sina Samangooei (ss@ecs.soton.ac.uk)

Constructor Summary

Constructors

Constructor and Description
CFMatrixUtils()

Method Summary

Modifier and Type	Method and Description
static gov.sandia.cognition.math.matrix.Matrix	abs(gov.sandia.cognition.math.matrix.Matrix mat) Create a new matrix with the absolute values of the input matrix.
static double	absSum(gov.sandia.cognition.math.matrix.Matrix mat) Compute the absolute sum of values in the matrix
static double	absSumSparse(gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix mat)
static double	absSumSparse(gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix mat)
static Jama.Matrix	asJama(gov.sandia.cognition.math.matrix.Matrix laplacian)
static gov.sandia.cognition.math.matrix.Matrix	asMat(com.jmatio.types.MLArray mlArray) Convert a matlab MLArray to a Matrix
static gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix	asSparseColumn(gov.sandia.cognition.math.matrix.Matrix a)
static gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix	asSparseRow(gov.sandia.cognition.math.matrix.Matrix a) Convert a Matrix to a SparseRowMatrix
static gov.sandia.cognition.math.matrix.Vector	colMean(gov.sandia.cognition.math.matrix.Matrix vt)
static double	colSparcity(gov.sandia.cognition.math.matrix.Matrix mat) Compute the proportion of completely zero columns to columns with non-zero values
static boolean	containsInfinity(gov.sandia.cognition.math.matrix.Matrix mat)
static boolean	containsNaN(gov.sandia.cognition.math.matrix.Matrix mat)
static boolean	containsNaN(gov.sandia.cognition.math.matrix.Vector vec)
static gov.sandia.cognition.math.matrix.Vector	diag(gov.sandia.cognition.math.matrix.Matrix mat) Extract the diagonal elements as a vector
static gov.sandia.cognition.math.matrix.Matrix	fastdot(gov.sandia.cognition.math.matrix.Matrix a, gov.sandia.cognition.math.matrix.Matrix b)
static gov.sandia.cognition.math.matrix.Matrix	fastminus(gov.sandia.cognition.math.matrix.Matrix A, gov.sandia.cognition.math.matrix.Matrix B)
static gov.sandia.cognition.math.matrix.Matrix	fastminusEquals(gov.sandia.cognition.math.matrix.Matrix A, gov.sandia.cognition.math.matrix.Matrix B)
static void	fastsetcol(gov.sandia.cognition.math.matrix.Matrix ret, int c, gov.sandia.cognition.math.matrix.Vector col)
static gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix	fastsparsedot(gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix a, gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix b)
static gov.sandia.cognition.math.matrix.Matrix	fastsparseminusEquals(gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix A, gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix B)
static gov.sandia.cognition.math.matrix.Matrix	fastsparseminusEquals(gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix A, gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix B)
static double[]	getData(gov.sandia.cognition.math.matrix.Matrix w) Get the data array backing this matrix (in column-major format)
static double	max(gov.sandia.cognition.math.matrix.Matrix u) Get the maximum element value
static double	max(gov.sandia.cognition.math.matrix.Vector column) Get the maximum element value
static double	min(gov.sandia.cognition.math.matrix.Matrix u) Get the minimum element value
static double	min(gov.sandia.cognition.math.matrix.Vector column) Get the minimum element value
static void	minusEqualsCol(gov.sandia.cognition.math.matrix.Matrix A, gov.sandia.cognition.math.matrix.Vector col)
static void	minusEqualsRow(gov.sandia.cognition.math.matrix.Matrix A, gov.sandia.cognition.math.matrix.Vector row)
static gov.sandia.cognition.math.matrix.Matrix	plusInplace(gov.sandia.cognition.math.matrix.Matrix mat, double etat) Add a constant to the matrix, returning the input matrix
static <T extends gov.sandia.cognition.math.matrix.Matrix> T	powInplace(T degree, double d) Bring each element to the power d
static <T extends gov.sandia.cognition.math.matrix.Vector> T	powInplace(T degree, double d) Bring each element to the power d
static gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix	randomSparseCol(int rows, int cols, double min, double max, double density, Random random) Create a random SparseColumnMatrix
static gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix	randomSparseRow(int rows, int cols, double min, double max, double density, Random random) Create a random SparseRowMatrix
static gov.sandia.cognition.math.matrix.Vector	rowMean(gov.sandia.cognition.math.matrix.Matrix vt)
static double	rowSparsity(gov.sandia.cognition.math.matrix.Matrix mat) Compute the proportion of completely zero rows to rows with non-zero values
static double	sparsity(gov.sandia.cognition.math.matrix.Matrix mat) Compute the sparsity
static double	sum(gov.sandia.cognition.math.matrix.Matrix A) Sum the matrix entries
static gov.sandia.cognition.math.matrix.Matrix	timesInplace(gov.sandia.cognition.math.matrix.Matrix mat, double etat) Multiply a matrix by a constant, storing the results in the input matrix.
static com.jmatio.types.MLArray	toMLArray(String name, gov.sandia.cognition.math.matrix.Matrix mat) Convert a matlab MLArray to a Matrix
static gov.sandia.cognition.math.matrix.Matrix	vstack(gov.sandia.cognition.math.matrix.Matrix... matricies) Stack matrices vertically
static gov.sandia.cognition.math.matrix.Matrix	vstack(gov.sandia.cognition.math.matrix.MatrixFactory<? extends gov.sandia.cognition.math.matrix.Matrix> matrixFactory, gov.sandia.cognition.math.matrix.Matrix... matricies) Stack matrices vertically

Methods inherited from class java.lang.Object

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

Constructor Detail

CFMatrixUtils

public CFMatrixUtils()

Method Detail

abs

public static gov.sandia.cognition.math.matrix.Matrix abs(gov.sandia.cognition.math.matrix.Matrix mat)

Create a new matrix with the absolute values of the input matrix.

Parameters:

mat - input matrix

Returns:

absolute matrix

absSum

public static double absSum(gov.sandia.cognition.math.matrix.Matrix mat)

Compute the absolute sum of values in the matrix

Parameters:

mat - the matrix

Returns:

the absolute sum

absSumSparse

public static double absSumSparse(gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix mat)

Parameters:

mat -

Returns:

sum of a SparseColumnMatrix

absSumSparse

public static double absSumSparse(gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix mat)

Parameters:

mat -

Returns:

sum of a SparseRowMatrix

timesInplace

public static gov.sandia.cognition.math.matrix.Matrix timesInplace(gov.sandia.cognition.math.matrix.Matrix mat,
                                                                   double etat)

Multiply a matrix by a constant, storing the results in the input matrix.

Parameters:

mat - the matrix

etat - the constant

Returns:

the input matrix

asMat

public static gov.sandia.cognition.math.matrix.Matrix asMat(com.jmatio.types.MLArray mlArray)

Convert a matlab MLArray to a Matrix

Parameters:

mlArray - the matrlab matrix

Returns:

the matrix

toMLArray

public static com.jmatio.types.MLArray toMLArray(String name,
                                                 gov.sandia.cognition.math.matrix.Matrix mat)

Convert a matlab MLArray to a Matrix

Parameters:

name -

mat -

Returns:

the matrix

rowSparsity

public static double rowSparsity(gov.sandia.cognition.math.matrix.Matrix mat)

Compute the proportion of completely zero rows to rows with non-zero values

Parameters:

mat - the matrix

Returns:

the row sparsity

colSparcity

public static double colSparcity(gov.sandia.cognition.math.matrix.Matrix mat)

Compute the proportion of completely zero columns to columns with non-zero values

Parameters:

mat - the matrix

Returns:

the column sparsity

plusInplace

public static gov.sandia.cognition.math.matrix.Matrix plusInplace(gov.sandia.cognition.math.matrix.Matrix mat,
                                                                  double etat)

Add a constant to the matrix, returning the input matrix

Parameters:

mat - the matrix

etat - the constant

Returns:

the matrix

diag

public static gov.sandia.cognition.math.matrix.Vector diag(gov.sandia.cognition.math.matrix.Matrix mat)

Extract the diagonal elements as a vector

Parameters:

mat - the matrix to extract from

Returns:

the diagonal

vstack

public static gov.sandia.cognition.math.matrix.Matrix vstack(gov.sandia.cognition.math.matrix.MatrixFactory<? extends gov.sandia.cognition.math.matrix.Matrix> matrixFactory,
                                                             gov.sandia.cognition.math.matrix.Matrix... matricies)

Stack matrices vertically

Parameters:

matrixFactory - factory to create output matrix

matricies - matrices to stack

Returns:

matrix created from the stacking

vstack

public static gov.sandia.cognition.math.matrix.Matrix vstack(gov.sandia.cognition.math.matrix.Matrix... matricies)

Stack matrices vertically

Parameters:

matricies - matrices to stack

Returns:

matrix created from the stacking

getData

public static double[] getData(gov.sandia.cognition.math.matrix.Matrix w)

Get the data array backing this matrix (in column-major format)

Parameters:

w - the matrix

Returns:

the data

min

public static double min(gov.sandia.cognition.math.matrix.Matrix u)

Get the minimum element value

Parameters:

u - the matrix

Returns:

the min value

max

public static double max(gov.sandia.cognition.math.matrix.Matrix u)

Get the maximum element value

Parameters:

u - the matrix

Returns:

the max value

min

public static double min(gov.sandia.cognition.math.matrix.Vector column)

Get the minimum element value

Parameters:

column - the vector

Returns:

the min value

max

public static double max(gov.sandia.cognition.math.matrix.Vector column)

Get the maximum element value

Parameters:

column - the vector

Returns:

the max value

sparsity

public static double sparsity(gov.sandia.cognition.math.matrix.Matrix mat)

Compute the sparsity

Parameters:

mat - the matrix

Returns:

the sparsity

powInplace

public static <T extends gov.sandia.cognition.math.matrix.Matrix> T powInplace(T degree,
                                                                               double d)

Bring each element to the power d

Parameters:

degree -

d -

Returns:

the input

powInplace

public static <T extends gov.sandia.cognition.math.matrix.Vector> T powInplace(T degree,
                                                                               double d)

Bring each element to the power d

Parameters:

degree -

d -

Returns:

the input

asJama

public static Jama.Matrix asJama(gov.sandia.cognition.math.matrix.Matrix laplacian)

Parameters:

laplacian -

Returns:

copy and convert

rowMean

public static gov.sandia.cognition.math.matrix.Vector rowMean(gov.sandia.cognition.math.matrix.Matrix vt)

Parameters:

vt -

Returns:

mean of each row

colMean

public static gov.sandia.cognition.math.matrix.Vector colMean(gov.sandia.cognition.math.matrix.Matrix vt)

Parameters:

vt -

Returns:

mean of each row

minusEqualsCol

public static void minusEqualsCol(gov.sandia.cognition.math.matrix.Matrix A,
                                  gov.sandia.cognition.math.matrix.Vector col)

Parameters:

A -

col -

minusEqualsRow

public static void minusEqualsRow(gov.sandia.cognition.math.matrix.Matrix A,
                                  gov.sandia.cognition.math.matrix.Vector row)

Parameters:

A -

row -

randomSparseCol

public static gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix randomSparseCol(int rows,
                                                                                      int cols,
                                                                                      double min,
                                                                                      double max,
                                                                                      double density,
                                                                                      Random random)

Create a random SparseColumnMatrix

Parameters:

rows - number of rows

cols - number of columns

min - the minimum value

max - the maximum value

density - the matrix density

random - the RNG

Returns:

the random matrix

randomSparseRow

public static gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix randomSparseRow(int rows,
                                                                                   int cols,
                                                                                   double min,
                                                                                   double max,
                                                                                   double density,
                                                                                   Random random)

Create a random SparseRowMatrix

Parameters:

rows - number of rows

cols - number of columns

min - the minimum value

max - the maximum value

density - the matrix density

random - the RNG

Returns:

the random matrix

fastsparsedot

public static gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix fastsparsedot(gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix a,
                                                                                 gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix b)

Parameters:

a -

b -

Returns:

performs a dot product taking advantage of the sparcity in b and a

fastdot

public static gov.sandia.cognition.math.matrix.Matrix fastdot(gov.sandia.cognition.math.matrix.Matrix a,
                                                              gov.sandia.cognition.math.matrix.Matrix b)

Parameters:

a -

b -

Returns:

checks for the fastest way to do this dot product

asSparseColumn

public static gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix asSparseColumn(gov.sandia.cognition.math.matrix.Matrix a)

Parameters:

a -

Returns:

turns the provided matrix into a SparseColumnMatrix

asSparseRow

public static gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix asSparseRow(gov.sandia.cognition.math.matrix.Matrix a)

Convert a Matrix to a SparseRowMatrix

Parameters:

a -

Returns:

the SparseRowMatrix

fastsetcol

public static void fastsetcol(gov.sandia.cognition.math.matrix.Matrix ret,
                              int c,
                              gov.sandia.cognition.math.matrix.Vector col)

Parameters:

ret -

c -

col -

fastminusEquals

public static gov.sandia.cognition.math.matrix.Matrix fastminusEquals(gov.sandia.cognition.math.matrix.Matrix A,
                                                                      gov.sandia.cognition.math.matrix.Matrix B)

Parameters:

A -

B -

Returns:

A - B, done using fastsparseminusEquals(SparseColumnMatrix, SparseColumnMatrix) if possible

fastminus

public static gov.sandia.cognition.math.matrix.Matrix fastminus(gov.sandia.cognition.math.matrix.Matrix A,
                                                                gov.sandia.cognition.math.matrix.Matrix B)

Parameters:

A -

B -

Returns:

A - B, done using fastminusEquals(Matrix, Matrix) if possible

fastsparseminusEquals

public static gov.sandia.cognition.math.matrix.Matrix fastsparseminusEquals(gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix A,
                                                                            gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix B)

Parameters:

A -

B -

Returns:

A - B

fastsparseminusEquals

public static gov.sandia.cognition.math.matrix.Matrix fastsparseminusEquals(gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix A,
                                                                            gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix B)

Parameters:

A -

B -

Returns:

A - B

containsNaN

public static boolean containsNaN(gov.sandia.cognition.math.matrix.Matrix mat)

Parameters:

mat -

Returns:

checks elements using Double.isNaN()

containsNaN

public static boolean containsNaN(gov.sandia.cognition.math.matrix.Vector vec)

Parameters:

vec -

Returns:

checks elements using Double.isNaN()

containsInfinity

public static boolean containsInfinity(gov.sandia.cognition.math.matrix.Matrix mat)

Parameters:

mat -

Returns:

checks elements using Double.isInfinite()

sum

public static double sum(gov.sandia.cognition.math.matrix.Matrix A)

Sum the matrix entries

Parameters:

A -

Returns:

the sum