/*
* Copyright 2011 David Jurgens
*
* This file is part of the S-Space package and is covered under the terms and
* conditions therein.
*
* The S-Space package is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License version 2 as published
* by the Free Software Foundation and distributed hereunder to you.
*
* THIS SOFTWARE IS PROVIDED "AS IS" AND NO REPRESENTATIONS OR WARRANTIES,
* EXPRESS OR IMPLIED ARE MADE. BY WAY OF EXAMPLE, BUT NOT LIMITATION, WE MAKE
* NO REPRESENTATIONS OR WARRANTIES OF MERCHANT- ABILITY OR FITNESS FOR ANY
* PARTICULAR PURPOSE OR THAT THE USE OF THE LICENSED SOFTWARE OR DOCUMENTATION
* WILL NOT INFRINGE ANY THIRD PARTY PATENTS, COPYRIGHTS, TRADEMARKS OR OTHER
* RIGHTS.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package edu.ucla.sspace.matrix;
import edu.ucla.sspace.vector.SparseHashDoubleVector;
import edu.ucla.sspace.vector.DoubleVector;
import edu.ucla.sspace.vector.SparseDoubleVector;
import edu.ucla.sspace.vector.Vector;
import edu.ucla.sspace.vector.Vectors;
/**
* A {@code SparseMatrix} backed by vectors that provide amortized O(1) access
* to their elements. Each row is implemented using a hashing-based vector.
* This class provides an alternate implementation to {@link YaleSparseMatrix};
* this class potentially uses more memory than {@code YaleSparseMatrix}, but
* provides O(1) access instead of O(log(n)). The size of this matrix is fixed,
* and attempts to access rows or columns beyond the size will throw an {@link
* IndexOutOfBoundsException}.
*
* @author David Jurgens
*/
public class SparseHashMatrix extends AbstractMatrix
implements SparseMatrix, java.io.Serializable {
private static final long serialVersionUID = 1L;
/**
* The number of rows contained in this {@code SparseMatrix}.
*/
private final int rows;
/**
* The number of columns contained in this {@code SparseMatrix}.
*/
private final int columns;
/**
* Each row is defined as a {@link SparseHashDoubleVector} which does most
* of the work.
*/
private final SparseHashDoubleVector[] sparseMatrix;
/**
* Constructs a sparse matrix with the specified dimensions.
*/
public SparseHashMatrix(int rows, int columns) {
this.rows = rows;
this.columns = columns;
sparseMatrix = new SparseHashDoubleVector[rows];
for (int r = 0; r < rows; ++r)
sparseMatrix[r] = new SparseHashDoubleVector(columns);
}
/**
* Checks that the indices are within the bounds of this matrix or throws an
* {@link IndexOutOfBoundsException} if not.
*/
private void checkIndices(int row, int col) {
if (row < 0 || col < 0 || row >= rows || col >= columns) {
throw new IndexOutOfBoundsException();
}
}
/**
* {@inheritDoc}
*/
@Override public int columns() {
return columns;
}
/**
* {@inheritDoc}
*/
@Override public SparseDoubleVector getColumnVector(int column) {
SparseHashDoubleVector col = new SparseHashDoubleVector(rows);
for (int r = 0; r < rows(); ++r)
col.set(r, getRowVector(r).get(column));
return col;
}
/**
* {@inheritDoc}
*/
@Override public SparseDoubleVector getRowVector(int row) {
return sparseMatrix[row];
}
/**
* {@inheritDoc}
*/
@Override public int rows() {
return rows;
}
/**
* {@inheritDoc}
*/
@Override public void set(int row, int col, double val) {
checkIndices(row, col);
sparseMatrix[row].set(col, val);
}
}