medusa.georgios.enhanced_mcl

Class SparseMatrix

java.lang.Object

java.util.AbstractCollection<E>

java.util.AbstractList<E>

java.util.ArrayList<SparseVector>

medusa.georgios.enhanced_mcl.SparseMatrix

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, java.lang.Iterable<SparseVector>, java.util.Collection<SparseVector>, java.util.List<SparseVector>, java.util.RandomAccess

public class SparseMatrix
extends java.util.ArrayList<SparseVector>

SparseMatrix is a sparse matrix with row-major format.

Conventions: except for the inherited methods and normalise(double), operations leave this ummodified (immutable) if there is a return value. Within operations, no pruning of values close to zero is done. Pruning can be controlled via the prune() method.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
SparseMatrix() empty sparse matrix
SparseMatrix(double[][] x) create sparse matrix from full matrix
SparseMatrix(int rows, int cols) empty sparse matrix with allocated number of rows
SparseMatrix(SparseMatrix matrix) copy contructor

Method Summary

Modifier and Type	Method and Description
double	add(int i, int j, double a) adds a to the specified element, growing the matrix if necessary.
void	adjustMaxIndex(int i, int j) adjusts the size of the matrix.
SparseMatrix	copy() copy the matrix and its elements
double	get(int i, int j) get number at index or 0.
SparseVector	getColum(int i) get a column of the sparse matrix (expensive).
double[][]	getDense() create dense representation
int[]	getSize() get the size of the matrix
void	hadamardPower(double s) mutable m2 = m .^ s
void	hadamardProduct(SparseMatrix m) mutable Hadamard product
SparseMatrix	matrixTimes(SparseMatrix m) immutable multiply matrix M with this (A) : M * A
SparseVector	normalise(double rowsum) normalise rows to rowsum
void	normaliseCols() normalise by minor dimension (columns), expensive.
void	normaliseRows() normalise by major dimension (rows)
void	prune(double threshold) prune all values whose magnitude is below threshold
double	set(int i, int j, double a) set the value at the index i,j, returning the old value or 0.
SparseVector	set(int i, SparseVector x) set the sparse vector at index i.
SparseMatrix	times(SparseMatrix m) immutable multiply this matrix (A) with M : A * M
SparseVector	times(SparseVector v) immutable multiply this times the vector: A * x, i.e., rowwise.
SparseMatrix	timesTransposed(SparseMatrix m) mutable multiply this matrix (A) with M : A * M'
java.lang.String	toString()
java.lang.String	toStringDense() prints a dense representation
SparseMatrix	transpose() immutable transpose.
SparseVector	vectorTimes(SparseVector v) immutable multiply the vector times this: x' * A, i.e., colwise.

Methods inherited from class java.util.ArrayList

add, add, addAll, addAll, clear, clone, contains, ensureCapacity, forEach, get, indexOf, isEmpty, iterator, lastIndexOf, listIterator, listIterator, remove, remove, removeAll, removeIf, replaceAll, retainAll, size, sort, spliterator, subList, toArray, toArray, trimToSize

Methods inherited from class java.util.AbstractList

equals, hashCode

Methods inherited from class java.util.AbstractCollection

containsAll

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.List

containsAll, equals, hashCode

Methods inherited from interface java.util.Collection

parallelStream, stream

Constructor Detail

SparseMatrix

public SparseMatrix()

empty sparse matrix

SparseMatrix

public SparseMatrix(int rows,
                    int cols)

empty sparse matrix with allocated number of rows

Parameters:

rows -

cols -

SparseMatrix

public SparseMatrix(double[][] x)

create sparse matrix from full matrix

Parameters:

x -

SparseMatrix

public SparseMatrix(SparseMatrix matrix)

copy contructor

Parameters:

matrix -

Method Detail

getDense

public double[][] getDense()

create dense representation

Returns:

set

public SparseVector set(int i,
                        SparseVector x)

set the sparse vector at index i.

Specified by:

set in interface java.util.List<SparseVector>

Overrides:

set in class java.util.ArrayList<SparseVector>

Parameters:

i -

x -

Returns:

the old value of the element

get

public double get(int i,
                  int j)

get number at index or 0. if not set. If index > size, returns 0.

Parameters:

i -

j -

Returns:

set

public double set(int i,
                  int j,
                  double a)

set the value at the index i,j, returning the old value or 0. Increase matrix size if index exceeds the dimension.

Parameters:

i -

j -

a -

Returns:

adjustMaxIndex

public void adjustMaxIndex(int i,
                           int j)

adjusts the size of the matrix.

Parameters:

i - index addressed

j - index addressed

getSize

public int[] getSize()

get the size of the matrix

Returns:

add

public double add(int i,
                  int j,
                  double a)

adds a to the specified element, growing the matrix if necessary.

Parameters:

i -

j -

a -

Returns:

new value

normalise

public SparseVector normalise(double rowsum)

normalise rows to rowsum

Parameters:

rowsum - for each row

Returns:

vector of old row sums

normaliseRows

public void normaliseRows()

normalise by major dimension (rows)

normaliseCols

public void normaliseCols()

normalise by minor dimension (columns), expensive.

copy

public SparseMatrix copy()

copy the matrix and its elements

times

public SparseVector times(SparseVector v)

immutable multiply this times the vector: A * x, i.e., rowwise.

Parameters:

v -

Returns:

vectorTimes

public SparseVector vectorTimes(SparseVector v)

immutable multiply the vector times this: x' * A, i.e., colwise.

Parameters:

v -

Returns:

timesTransposed

public SparseMatrix timesTransposed(SparseMatrix m)

mutable multiply this matrix (A) with M : A * M'

Parameters:

m -

Returns:

modified this

times

public SparseMatrix times(SparseMatrix m)

immutable multiply this matrix (A) with M : A * M

Parameters:

m -

Returns:

matrix product

matrixTimes

public SparseMatrix matrixTimes(SparseMatrix m)

immutable multiply matrix M with this (A) : M * A

Parameters:

m -

Returns:

transpose

public SparseMatrix transpose()

immutable transpose.

Returns:

getColum

public SparseVector getColum(int i)

get a column of the sparse matrix (expensive).

Returns:

hadamardProduct

public void hadamardProduct(SparseMatrix m)

mutable Hadamard product

Parameters:

m -

hadamardPower

public void hadamardPower(double s)

mutable m2 = m .^ s

Parameters:

s -

toString

public java.lang.String toString()

Overrides:

toString in class java.util.AbstractCollection<SparseVector>

toStringDense

public java.lang.String toStringDense()

prints a dense representation

Returns:

prune

public void prune(double threshold)

prune all values whose magnitude is below threshold