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/*
* File: DenseMatrix.java
* Authors: Kevin R. Dixon
* Company: Sandia National Laboratories
* Project: Cognitive Foundry
*
* Copyright February 21, 2006, Sandia Corporation. Under the terms of Contract
* DE-AC04-94AL85000, there is a non-exclusive license for use of this work by
* or on behalf of the U.S. Government. Export of this program may require a
* license from the United States Government. See CopyrightHistory.txt for
* complete details.
*
*/
package gov.sandia.cognition.math.matrix.mtj;
import gov.sandia.cognition.annotation.CodeReview;
import gov.sandia.cognition.annotation.CodeReviewResponse;
import gov.sandia.cognition.annotation.PublicationReference;
import gov.sandia.cognition.annotation.PublicationType;
import gov.sandia.cognition.math.matrix.mtj.decomposition.SingularValueDecompositionMTJ;
import gov.sandia.cognition.math.matrix.Matrix;
import gov.sandia.cognition.math.matrix.MatrixEntry;
import gov.sandia.cognition.math.matrix.MatrixReader;
import gov.sandia.cognition.math.matrix.Vector;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.io.Serializable;
import java.text.NumberFormat;
/**
* Matrix that represents all its entries using a fixed-size storage scheme,
* based on MTJ's DenseMatrix storage class. Fast iteration, access, and
* arithmetic, but storage size scale with the size of the number of rows and
* columns.
*
* To create a new DenseMatrix, please use the DenseMatrixFactoryMTJ static
* calls, or the DefaultRingFactory class. This is there to provide a layer
* of abstraction and make it easier for people to drop in new matrix packages
*
* @author Kevin R. Dixon
* @since 1.0
*
*/
@CodeReview(
reviewer="Jonathan McClain",
date="2006-05-19",
changesNeeded=true,
comments="Comments indicated with / / / ",
response=@CodeReviewResponse(
respondent="Kevin R. Dixon",
date="2006-05-22",
moreChangesNeeded=false,
comments="Fixed comments for writeObject and readObject"
)
)
@PublicationReference(
author="Bjorn-Ove Heimsund",
title="Matrix Toolkits for Java DenseMatrix",
type=PublicationType.WebPage,
year=2006,
url="http://ressim.berlios.de/doc/no/uib/cipr/matrix/DenseMatrix.html",
notes="This class wraps the DenseMatrix class from Heimsund's MTJ package"
)
public class DenseMatrix
extends AbstractMTJMatrix
implements Serializable
{
/**
* Creates a new instance of DenseMatrix
* @param numRows number of rows in the matrix
* @param numColumns number of columns in the matrix
*/
protected DenseMatrix(
int numRows,
int numColumns )
{
super( new no.uib.cipr.matrix.DenseMatrix( numRows, numColumns ) );
}
/**
* Creates a new instance of DenseMatrix
* @param internalMatrix Internal MTJ-based matrix
*/
protected DenseMatrix(
no.uib.cipr.matrix.DenseMatrix internalMatrix )
{
super( internalMatrix );
}
/**
* Creates a new instance of DenseMatrix
* @param matrix Matrix from which to pull data, will not be modified
*/
protected DenseMatrix(
Matrix matrix )
{
this( matrix.getNumRows(), matrix.getNumColumns() );
for (MatrixEntry e : matrix)
{
this.setElement( e.getRowIndex(), e.getColumnIndex(),
e.getValue() );
}
}
/**
* Creates a new instance of DenseMatrix
* @param matrix DenseMatrix from which to pull data, will not be modified
*/
protected DenseMatrix(
DenseMatrix matrix )
{
this( new no.uib.cipr.matrix.DenseMatrix(
(no.uib.cipr.matrix.DenseMatrix) matrix.getInternalMatrix().copy() ) );
}
/**
* Creates a new instance of DenseMatrix
* @param reader takes in information from a java stream
* @throws java.io.IOException if the stream is invalid
*/
protected DenseMatrix(
MatrixReader reader ) throws IOException
{
this( reader.read() );
}
@Override
public DenseMatrix clone()
{
return (DenseMatrix) super.clone();
}
public DenseMatrix times(
final AbstractMTJMatrix matrix )
{
int returnRows = this.getNumRows();
int returnColumns = matrix.getNumColumns();
DenseMatrix retval = new DenseMatrix( returnRows, returnColumns );
this.timesInto( matrix, retval );
return retval;
}
public DenseVector times(
final AbstractMTJVector vector )
{
DenseVector answer = new DenseVector( this.getNumRows() );
this.timesInto( vector, answer );
return answer;
}
/**
* Solve for "X" in the equation: this*X = B
* @param B must satisfy this.getNumRows() == B.numRows()
* @param X must satisfy this.getNumColumns() == X.getNumRows()
*/
protected void solveInto(
final DenseMatrix B,
DenseMatrix X )
{
this.getInternalMatrix().solve(
B.getInternalMatrix(), X.getInternalMatrix() );
}
/**
* Solve for "x" in the equation: this*x = b
* @param b must satisfy this.getNumRows() == b.getDimensionality()
* @param x must satisfy this.getNumColumns() == x.getDimensionality()
*/
protected void solveInto(
final DenseVector b,
DenseVector x )
{
this.getInternalMatrix().solve(
b.getInternalVector(), x.getInternalVector() );
}
public DenseMatrix pseudoInverse(
double effectiveZero )
{
SingularValueDecompositionMTJ svd =
SingularValueDecompositionMTJ.create( this );
return (DenseMatrix) svd.pseudoInverse( effectiveZero );
}
public DenseMatrix getSubMatrix(
int minRow,
int maxRow,
int minColumn,
int maxColumn )
{
int numRows = maxRow - minRow + 1;
if (numRows <= 0)
{
throw new IllegalArgumentException( "minRow " + minRow +
" >= maxRow " + maxRow );
}
int numColumns = maxColumn - minColumn + 1;
if (numColumns <= 0)
{
throw new IllegalArgumentException( "minCol " + minColumn +
" >= maxCol " + maxColumn );
}
DenseMatrix submatrix = new DenseMatrix( numRows, numColumns );
this.getSubMatrixInto(
minRow, maxRow, minColumn, maxColumn, submatrix );
return submatrix;
}
public DenseMatrix transpose()
{
DenseMatrix retval = new DenseMatrix(
this.getNumColumns(), this.getNumRows() );
this.transposeInto( retval );
return retval;
}
/**
* Writes the DenseMatrix out as a matrix of values (no indices are printed)
* @return String representing the DenseMatrix
*/
@Override
public String toString()
{
final StringBuilder result =
new StringBuilder(this.getNumRows() * this.getNumColumns() * 10);
for (int i = 0; i < this.getNumRows(); i++)
{
for (int j = 0; j < this.getNumColumns(); j++)
{
result.append(" ");
result.append(this.getElement(i, j));
}
result.append("\n");
}
return result.toString();
}
public String toString(
final NumberFormat format)
{
final StringBuilder result =
new StringBuilder(this.getNumRows() * this.getNumColumns() * 5);
for (int i = 0; i < this.getNumRows(); i++)
{
for (int j = 0; j < this.getNumColumns(); j++)
{
result.append(" ");
result.append(format.format(this.getElement(i, j)));
}
result.append("\n");
}
return result.toString();
}
public DenseVector getColumn(
int columnIndex )
{
int M = this.getNumRows();
DenseVector columnVector = new DenseVector( M );
this.getColumnInto( columnIndex, columnVector );
return columnVector;
}
public DenseVector getRow(
int rowIndex )
{
int N = this.getNumColumns();
DenseVector rowVector = new DenseVector( N );
this.getRowInto( rowIndex, rowVector );
return rowVector;
}
/**
* Writes a DenseMatrix out to a serialized file
* @param out output stream to which the DenseMatrix will be written
* @throws java.io.IOException On bad write
*/
private void writeObject(
ObjectOutputStream out )
throws IOException
{
out.defaultWriteObject();
//manually serialize superclass
int numRows = this.getNumRows();
int numColumns = this.getNumColumns();
double[][] data = new double[numRows][numColumns];
for (int i = 0; i < numRows; i++)
{
for (int j = 0; j < numColumns; j++)
{
data[i][j] = this.getElement( i, j );
}
}
out.writeObject( data );
}
/**
* Reads in a serialized class from the specified stream
* @param in stream from which to read the DenseMatrix
* @throws java.io.IOException On bad read
* @throws java.lang.ClassNotFoundException if next object isn't DenseMatrix
*/
private void readObject(
ObjectInputStream in )
throws IOException, ClassNotFoundException
{
in.defaultReadObject();
double[][] data = (double[][]) in.readObject();
this.setInternalMatrix(
new no.uib.cipr.matrix.DenseMatrix( data ) );
}
/**
* Gets the underlying double array from the MTJ matrix
* @return double array from the underlying MTJ matrix
*/
protected double[] getArray()
{
return ((no.uib.cipr.matrix.DenseMatrix) this.getInternalMatrix()).getData();
}
@Override
public DenseVector convertToVector()
{
return new DenseVector( this.getArray() );
}
@Override
public void convertFromVector(
Vector parameters )
{
if (parameters instanceof DenseVector)
{
this.convertFromVector( (DenseVector) parameters );
}
else
{
super.convertFromVector( parameters );
}
}
/**
* Incorporates the parameters in the given vector back into the object.
*
* @param parameters The parameters to incorporate.
*/
public void convertFromVector(
DenseVector parameters )
{
double[] myParameters = this.getArray();
double[] vectorParameters = parameters.getArray();
if (myParameters.length != vectorParameters.length)
{
throw new IllegalArgumentException( "Dimensions do not match" );
}
for (int i = 0; i < myParameters.length; i++)
{
myParameters[i] = vectorParameters[i];
}
}
}
