cern.colt.matrix.impl

Class SparseDoubleMatrix2D

java.lang.Object

cern.colt.PersistentObject

cern.colt.matrix.impl.AbstractMatrix

cern.colt.matrix.impl.AbstractMatrix2D

cern.colt.matrix.DoubleMatrix2D

cern.colt.matrix.impl.SparseDoubleMatrix2D

All Implemented Interfaces:

Serializable, Cloneable

public class SparseDoubleMatrix2D
extends DoubleMatrix2D

Sparse hashed 2-d matrix holding double elements. First see the package summary and javadoc tree view to get the broad picture.

Implementation:

Note that this implementation is not synchronized. Uses a OpenIntDoubleHashMap, which is a compact and performant hashing technique.

Memory requirements:

Cells that

• are never set to non-zero values do not use any memory.
• switch from zero to non-zero state do use memory.
• switch back from non-zero to zero state also do use memory. However, their memory is automatically reclaimed from time to time. It can also manually be reclaimed by calling trimToSize().

worst case: memory [bytes] = (1/minLoadFactor) * nonZeros * 13.
best case: memory [bytes] = (1/maxLoadFactor) * nonZeros * 13.
Where nonZeros = cardinality() is the number of non-zero cells. Thus, a 1000 x 1000 matrix with minLoadFactor=0.25 and maxLoadFactor=0.5 and 1000000 non-zero cells consumes between 25 MB and 50 MB. The same 1000 x 1000 matrix with 1000 non-zero cells consumes between 25 and 50 KB.

Time complexity:

This class offers expected time complexity O(1) (i.e. constant time) for the basic operations get, getQuick, set, setQuick and size assuming the hash function disperses the elements properly among the buckets. Otherwise, pathological cases, although highly improbable, can occur, degrading performance to O(N) in the worst case. As such this sparse class is expected to have no worse time complexity than its dense counterpart DenseDoubleMatrix2D. However, constant factors are considerably larger.

Cells are internally addressed in row-major. Performance sensitive applications can exploit this fact. Setting values in a loop row-by-row is quicker than column-by-column, because fewer hash collisions occur. Thus

        for (int row=0; row < rows; row++) {
                for (int column=0; column < columns; column++) {
                        matrix.setQuick(row,column,someValue);
                }
        }

is quicker than

        for (int column=0; column < columns; column++) {
                for (int row=0; row < rows; row++) {
                        matrix.setQuick(row,column,someValue);
                }
        }

Version:

1.0, 09/24/99

Author:

wolfgang.hoschek@cern.ch

See Also:

cern.colt.map, OpenIntDoubleHashMap, Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected int	dummy
protected AbstractIntDoubleMap	elements

Fields inherited from class cern.colt.matrix.impl.AbstractMatrix2D

columns, columnStride, columnZero, rows, rowStride, rowZero

Fields inherited from class cern.colt.matrix.impl.AbstractMatrix

isNoView

Fields inherited from class cern.colt.PersistentObject

serialVersionUID

Constructor Summary

Constructors

Modifier	Constructor and Description
	SparseDoubleMatrix2D(double[][] values) Constructs a matrix with a copy of the given values.
	SparseDoubleMatrix2D(int rows, int columns) Constructs a matrix with a given number of rows and columns and default memory usage.
protected	SparseDoubleMatrix2D(int rows, int columns, AbstractIntDoubleMap elements, int rowZero, int columnZero, int rowStride, int columnStride) Constructs a view with the given parameters.
	SparseDoubleMatrix2D(int rows, int columns, int initialCapacity, double minLoadFactor, double maxLoadFactor) Constructs a matrix with a given number of rows and columns using memory as specified.

Method Summary

Methods

Modifier and Type	Method and Description
DoubleMatrix2D	assign(double value) Sets all cells to the state specified by value.
DoubleMatrix2D	assign(DoubleFunction function) Assigns the result of a function to each cell; x[row,col] = function(x[row,col]).
DoubleMatrix2D	assign(DoubleMatrix2D source) Replaces all cell values of the receiver with the values of another matrix.
DoubleMatrix2D	assign(DoubleMatrix2D y, DoubleDoubleFunction function) Assigns the result of a function to each cell; x[row,col] = function(x[row,col],y[row,col]).
int	cardinality() Returns the number of cells having non-zero values.
void	ensureCapacity(int minCapacity) Ensures that the receiver can hold at least the specified number of non-zero cells without needing to allocate new internal memory.
DoubleMatrix2D	forEachNonZero(IntIntDoubleFunction function) Assigns the result of a function to each non-zero cell; x[row,col] = function(x[row,col]).
double	getQuick(int row, int column) Returns the matrix cell value at coordinate [row,column].
protected boolean	haveSharedCellsRaw(DoubleMatrix2D other) Returns true if both matrices share common cells.
protected int	index(int row, int column) Returns the position of the given coordinate within the (virtual or non-virtual) internal 1-dimensional array.
DoubleMatrix2D	like(int rows, int columns) Construct and returns a new empty matrix of the same dynamic type as the receiver, having the specified number of rows and columns.
DoubleMatrix1D	like1D(int size) Construct and returns a new 1-d matrix of the corresponding dynamic type, entirelly independent of the receiver.
protected DoubleMatrix1D	like1D(int size, int offset, int stride) Construct and returns a new 1-d matrix of the corresponding dynamic type, sharing the same cells.
void	setQuick(int row, int column, double value) Sets the matrix cell at coordinate [row,column] to the specified value.
void	trimToSize() Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
protected DoubleMatrix2D	viewSelectionLike(int[] rowOffsets, int[] columnOffsets) Construct and returns a new selection view.
DoubleMatrix1D	zMult(DoubleMatrix1D y, DoubleMatrix1D z, double alpha, double beta, boolean transposeA) Linear algebraic matrix-vector multiplication; z = alpha * A * y + beta*z.
DoubleMatrix2D	zMult(DoubleMatrix2D B, DoubleMatrix2D C, double alpha, double beta, boolean transposeA, boolean transposeB) Linear algebraic matrix-matrix multiplication; C = alpha * A x B + beta*C.

Methods inherited from class cern.colt.matrix.DoubleMatrix2D

aggregate, aggregate, assign, copy, equals, equals, get, getContent, getNonZeros, haveSharedCells, like, set, toArray, toString, view, viewColumn, viewColumnFlip, viewDice, viewPart, viewRow, viewRowFlip, viewSelection, viewSelection, viewSorted, viewStrides, zAssign8Neighbors, zMult, zMult, zSum

Methods inherited from class cern.colt.matrix.impl.AbstractMatrix2D

_columnOffset, _columnRank, _rowOffset, _rowRank, checkBox, checkColumn, checkColumnIndexes, checkRow, checkRowIndexes, checkShape, checkShape, columns, rows, setUp, setUp, size, toStringShort, vColumnFlip, vDice, vPart, vRowFlip, vStrides

Methods inherited from class cern.colt.matrix.impl.AbstractMatrix

isView

Methods inherited from class cern.colt.PersistentObject

clone

Methods inherited from class java.lang.Object

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

Field Detail

elements

protected AbstractIntDoubleMap elements

dummy

protected int dummy

Constructor Detail

SparseDoubleMatrix2D

public SparseDoubleMatrix2D(double[][] values)

Constructs a matrix with a copy of the given values. values is required to have the form values[row][column] and have exactly the same number of columns in every row.

The values are copied. So subsequent changes in values are not reflected in the matrix, and vice-versa.

Parameters:

values - The values to be filled into the new matrix.

Throws:

IllegalArgumentException - if for any 1 <= row < values.length: values[row].length != values[row-1].length.

SparseDoubleMatrix2D

public SparseDoubleMatrix2D(int rows,
                    int columns)

Constructs a matrix with a given number of rows and columns and default memory usage. All entries are initially 0.

Parameters:

rows - the number of rows the matrix shall have.

columns - the number of columns the matrix shall have.

Throws:

IllegalArgumentException - if rows<0 || columns<0 || (double)columns*rows > Integer.MAX_VALUE.

SparseDoubleMatrix2D

public SparseDoubleMatrix2D(int rows,
                    int columns,
                    int initialCapacity,
                    double minLoadFactor,
                    double maxLoadFactor)

Constructs a matrix with a given number of rows and columns using memory as specified. All entries are initially 0. For details related to memory usage see OpenIntDoubleHashMap.

Parameters:

rows - the number of rows the matrix shall have.

columns - the number of columns the matrix shall have.

initialCapacity - the initial capacity of the hash map. If not known, set initialCapacity=0 or small.

minLoadFactor - the minimum load factor of the hash map.

maxLoadFactor - the maximum load factor of the hash map.

Throws:

IllegalArgumentException - if initialCapacity < 0 || (minLoadFactor < 0.0 || minLoadFactor >= 1.0) || (maxLoadFactor <= 0.0 || maxLoadFactor >= 1.0) || (minLoadFactor >= maxLoadFactor).

IllegalArgumentException - if rows<0 || columns<0 || (double)columns*rows > Integer.MAX_VALUE.

SparseDoubleMatrix2D

protected SparseDoubleMatrix2D(int rows,
                    int columns,
                    AbstractIntDoubleMap elements,
                    int rowZero,
                    int columnZero,
                    int rowStride,
                    int columnStride)

Constructs a view with the given parameters.

Parameters:

rows - the number of rows the matrix shall have.

columns - the number of columns the matrix shall have.

elements - the cells.

rowZero - the position of the first element.

columnZero - the position of the first element.

rowStride - the number of elements between two rows, i.e. index(i+1,j)-index(i,j).

columnStride - the number of elements between two columns, i.e. index(i,j+1)-index(i,j).

Throws:

IllegalArgumentException - if rows<0 || columns<0 || (double)columns*rows > Integer.MAX_VALUE or flip's are illegal.

Method Detail

assign

public DoubleMatrix2D assign(double value)

Sets all cells to the state specified by value.

Overrides:

assign in class DoubleMatrix2D

Parameters:

value - the value to be filled into the cells.

Returns:

this (for convenience only).

assign

public DoubleMatrix2D assign(DoubleFunction function)

Assigns the result of a function to each cell; x[row,col] = function(x[row,col]).

Example:

matrix = 2 x 2 matrix
0.5 1.5      
2.5 3.5

// change each cell to its sine
matrix.assign(cern.jet.math.Functions.sin);
-->
2 x 2 matrix
0.479426  0.997495 
0.598472 -0.350783

For further examples, see the package doc.

Overrides:

assign in class DoubleMatrix2D

Parameters:

function - a function object taking as argument the current cell's value.

Returns:

this (for convenience only).

See Also:

Functions

assign

public DoubleMatrix2D assign(DoubleMatrix2D source)

Replaces all cell values of the receiver with the values of another matrix. Both matrices must have the same number of rows and columns. If both matrices share the same cells (as is the case if they are views derived from the same matrix) and intersect in an ambiguous way, then replaces as if using an intermediate auxiliary deep copy of other.

Overrides:

assign in class DoubleMatrix2D

Parameters:

source - the source matrix to copy from (may be identical to the receiver).

Returns:

this (for convenience only).

Throws:

IllegalArgumentException - if columns() != source.columns() || rows() != source.rows()

assign

public DoubleMatrix2D assign(DoubleMatrix2D y,
                    DoubleDoubleFunction function)

Description copied from class: DoubleMatrix2D

Assigns the result of a function to each cell; x[row,col] = function(x[row,col],y[row,col]).

Example:

// assign x[row,col] = x[row,col]y[row,col]
m1 = 2 x 2 matrix 
0 1 
2 3

m2 = 2 x 2 matrix 
0 2 
4 6

m1.assign(m2, cern.jet.math.Functions.pow);
-->
m1 == 2 x 2 matrix
 1   1 
16 729

For further examples, see the package doc.

Overrides:

assign in class DoubleMatrix2D

Parameters:

y - the secondary matrix to operate on.

function - a function object taking as first argument the current cell's value of this, and as second argument the current cell's value of y,

Returns:

this (for convenience only).

See Also:

Functions

cardinality

public int cardinality()

Returns the number of cells having non-zero values.

Overrides:

cardinality in class DoubleMatrix2D

ensureCapacity

public void ensureCapacity(int minCapacity)

Ensures that the receiver can hold at least the specified number of non-zero cells without needing to allocate new internal memory. If necessary, allocates new internal memory and increases the capacity of the receiver.

This method never need be called; it is for performance tuning only. Calling this method before tt>set()ing a large number of non-zero values boosts performance, because the receiver will grow only once instead of potentially many times and hash collisions get less probable.

Overrides:

ensureCapacity in class AbstractMatrix

Parameters:

minNonZeros - the desired minimum number of non-zero cells.

forEachNonZero

public DoubleMatrix2D forEachNonZero(IntIntDoubleFunction function)

Description copied from class: DoubleMatrix2D

Assigns the result of a function to each non-zero cell; x[row,col] = function(x[row,col]). Use this method for fast special-purpose iteration. If you want to modify another matrix instead of this (i.e. work in read-only mode), simply return the input value unchanged. Parameters to function are as follows: first==row, second==column, third==nonZeroValue.

Overrides:

forEachNonZero in class DoubleMatrix2D

Parameters:

function - a function object taking as argument the current non-zero cell's row, column and value.

Returns:

this (for convenience only).

getQuick

public double getQuick(int row,
              int column)

Returns the matrix cell value at coordinate [row,column].

Provided with invalid parameters this method may return invalid objects without throwing any exception. You should only use this method when you are absolutely sure that the coordinate is within bounds. Precondition (unchecked): 0 <= column < columns() && 0 <= row < rows().

Specified by:

getQuick in class DoubleMatrix2D

Parameters:

row - the index of the row-coordinate.

column - the index of the column-coordinate.

Returns:

the value at the specified coordinate.

haveSharedCellsRaw

protected boolean haveSharedCellsRaw(DoubleMatrix2D other)

Returns true if both matrices share common cells. More formally, returns true if at least one of the following conditions is met

• the receiver is a view of the other matrix
• the other matrix is a view of the receiver
• this == other

Overrides:

haveSharedCellsRaw in class DoubleMatrix2D

index

protected int index(int row,
        int column)

Returns the position of the given coordinate within the (virtual or non-virtual) internal 1-dimensional array.

Overrides:

index in class AbstractMatrix2D

Parameters:

row - the index of the row-coordinate.

column - the index of the column-coordinate.

like

public DoubleMatrix2D like(int rows,
                  int columns)

Construct and returns a new empty matrix of the same dynamic type as the receiver, having the specified number of rows and columns. For example, if the receiver is an instance of type DenseDoubleMatrix2D the new matrix must also be of type DenseDoubleMatrix2D, if the receiver is an instance of type SparseDoubleMatrix2D the new matrix must also be of type SparseDoubleMatrix2D, etc. In general, the new matrix should have internal parametrization as similar as possible.

Specified by:

like in class DoubleMatrix2D

Parameters:

rows - the number of rows the matrix shall have.

columns - the number of columns the matrix shall have.

Returns:

a new empty matrix of the same dynamic type.

like1D

public DoubleMatrix1D like1D(int size)

Construct and returns a new 1-d matrix of the corresponding dynamic type, entirelly independent of the receiver. For example, if the receiver is an instance of type DenseDoubleMatrix2D the new matrix must be of type DenseDoubleMatrix1D, if the receiver is an instance of type SparseDoubleMatrix2D the new matrix must be of type SparseDoubleMatrix1D, etc.

Specified by:

like1D in class DoubleMatrix2D

Parameters:

size - the number of cells the matrix shall have.

Returns:

a new matrix of the corresponding dynamic type.

like1D

protected DoubleMatrix1D like1D(int size,
                    int offset,
                    int stride)

Construct and returns a new 1-d matrix of the corresponding dynamic type, sharing the same cells. For example, if the receiver is an instance of type DenseDoubleMatrix2D the new matrix must be of type DenseDoubleMatrix1D, if the receiver is an instance of type SparseDoubleMatrix2D the new matrix must be of type SparseDoubleMatrix1D, etc.

Specified by:

like1D in class DoubleMatrix2D

Parameters:

size - the number of cells the matrix shall have.

offset - the index of the first element.

stride - the number of indexes between any two elements, i.e. index(i+1)-index(i).

Returns:

a new matrix of the corresponding dynamic type.

setQuick

public void setQuick(int row,
            int column,
            double value)

Sets the matrix cell at coordinate [row,column] to the specified value.

Provided with invalid parameters this method may access illegal indexes without throwing any exception. You should only use this method when you are absolutely sure that the coordinate is within bounds. Precondition (unchecked): 0 <= column < columns() && 0 <= row < rows().

Specified by:

setQuick in class DoubleMatrix2D

Parameters:

row - the index of the row-coordinate.

column - the index of the column-coordinate.

value - the value to be filled into the specified cell.

trimToSize

public void trimToSize()

Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.

Background:

Cells that

• are never set to non-zero values do not use any memory.
• switch from zero to non-zero state do use memory.
• switch back from non-zero to zero state also do use memory. However, their memory can be reclaimed by calling trimToSize().

A sequence like set(r,c,5); set(r,c,0); sets a cell to non-zero state and later back to zero state. Such as sequence generates obsolete memory that is automatically reclaimed from time to time or can manually be reclaimed by calling trimToSize(). Putting zeros into cells already containing zeros does not generate obsolete memory since no memory was allocated to them in the first place.

Overrides:

trimToSize in class AbstractMatrix

viewSelectionLike

protected DoubleMatrix2D viewSelectionLike(int[] rowOffsets,
                               int[] columnOffsets)

Construct and returns a new selection view.

Specified by:

viewSelectionLike in class DoubleMatrix2D

Parameters:

rowOffsets - the offsets of the visible elements.

columnOffsets - the offsets of the visible elements.

Returns:

a new view.

zMult

public DoubleMatrix1D zMult(DoubleMatrix1D y,
                   DoubleMatrix1D z,
                   double alpha,
                   double beta,
                   boolean transposeA)

Description copied from class: DoubleMatrix2D

Linear algebraic matrix-vector multiplication; z = alpha * A * y + beta*z. z[i] = alpha*Sum(A[i,j] * y[j]) + beta*z[i], i=0..A.rows()-1, j=0..y.size()-1. Where A == this.
Note: Matrix shape conformance is checked after potential transpositions.

Overrides:

zMult in class DoubleMatrix2D

Parameters:

y - the source vector.

z - the vector where results are to be stored. Set this parameter to null to indicate that a new result vector shall be constructed.

Returns:

z (for convenience only).

zMult

public DoubleMatrix2D zMult(DoubleMatrix2D B,
                   DoubleMatrix2D C,
                   double alpha,
                   double beta,
                   boolean transposeA,
                   boolean transposeB)

Description copied from class: DoubleMatrix2D

Linear algebraic matrix-matrix multiplication; C = alpha * A x B + beta*C. C[i,j] = alpha*Sum(A[i,k] * B[k,j]) + beta*C[i,j], k=0..n-1.
Matrix shapes: A(m x n), B(n x p), C(m x p).
Note: Matrix shape conformance is checked after potential transpositions.

Overrides:

zMult in class DoubleMatrix2D

Parameters:

B - the second source matrix.

C - the matrix where results are to be stored. Set this parameter to null to indicate that a new result matrix shall be constructed.

Returns:

C (for convenience only).