de.uni_leipzig.mcl.cluster
Class SparseMatrix

java.lang.Object
  java.util.AbstractCollection<E>
      java.util.AbstractList<E>
          java.util.ArrayList<SparseVector>
              de.uni_leipzig.mcl.cluster.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.

Author:

gregor :: arbylon . net

See Also:

Serialized Form

Field Summary

Fields inherited from class java.util.AbstractList

modCount

Constructor Summary

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

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()
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, get, indexOf, isEmpty, lastIndexOf, remove, remove, removeRange, size, toArray, toArray, trimToSize

Methods inherited from class java.util.AbstractList

equals, hashCode, iterator, listIterator, listIterator, subList

Methods inherited from class java.util.AbstractCollection

containsAll, removeAll, retainAll

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.List

containsAll, equals, hashCode, iterator, listIterator, listIterator, removeAll, retainAll, subList

Constructor Detail

SparseMatrix

public SparseMatrix()

empty sparse matrix

SparseMatrix

public SparseMatrix(double[][] x)

create sparse matrix from full matrix

Parameters:

x -

SparseMatrix

public SparseMatrix(int rows,
                    int cols)

empty sparse matrix with allocated number of rows

Parameters:

rows -

cols -

SparseMatrix

public SparseMatrix(SparseMatrix matrix)

copy contructor

Parameters:

matrix -

Method Detail

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

adjustMaxIndex

public void adjustMaxIndex(int i,
                           int j)

adjusts the size of the matrix.

Parameters:

i - index addressed

j - index addressed

copy

public SparseMatrix copy()

copy the matrix and its elements

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:

getColum

public SparseVector getColum(int i)

get a column of the sparse matrix (expensive).

Returns:

getDense

public double[][] getDense()

create dense representation

Returns:

getSize

public int[] getSize()

get the size of the matrix

Returns:

hadamardPower

public void hadamardPower(double s)

mutable m2 = m .^ s

Parameters:

s -

hadamardProduct

public void hadamardProduct(SparseMatrix m)

mutable Hadamard product

Parameters:

m -

matrixTimes

public SparseMatrix matrixTimes(SparseMatrix m)

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

Parameters:

m -

Returns:

normalise

public SparseVector normalise(double rowsum)

normalise rows to rowsum

Parameters:

rowsum - for each row

Returns:

vector of old row sums

normaliseCols

public void normaliseCols()

normalise by minor dimension (columns), expensive.

normaliseRows

public void normaliseRows()

normalise by major dimension (rows)

prune

public void prune(double threshold)

prune all values whose magnitude is below threshold

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:

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

times

public SparseMatrix times(SparseMatrix m)

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

Parameters:

m -

Returns:

matrix product

times

public SparseVector times(SparseVector v)

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

Parameters:

v -

Returns:

timesTransposed

public SparseMatrix timesTransposed(SparseMatrix m)

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

Parameters:

m -

Returns:

modified this

toString

public java.lang.String toString()

Overrides:

toString in class java.util.AbstractCollection<SparseVector>

transpose

public SparseMatrix transpose()

immutable transpose.

Returns:

vectorTimes

public SparseVector vectorTimes(SparseVector v)

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

Parameters:

v -

Returns: