edu.ucla.sspace.matrix.DiagonalMatrix Maven / Gradle / Ivy

Go to download

Show more of this group Show more artifacts with this name
Show all versions of sspace Show documentation

The S-Space Package is a Natural Language Processing library for distributional semantics representations. Distributional semantics representations model the meaning of words, phrases, and sentences as high dimensional vectors or probability distributions. The library includes common algorithms such as Latent Semantic Analysis, Random Indexing, and Latent Dirichlet Allocation. The S-Space package also includes software libraries for matrices, vectors, graphs, and numerous clustering algorithms.

The newest version!

/*
 * Copyright 2009 Keith Stevens 
 *
 * 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 .
 */

package edu.ucla.sspace.matrix;

import edu.ucla.sspace.vector.DoubleVector;
import edu.ucla.sspace.vector.SparseDoubleVector;
import edu.ucla.sspace.vector.SparseHashDoubleVector;


/**
 * A special-case {@code Matrix} implementation for diagonal matrices. This
 * class provides a memory efficient representation and additional bounds
 * checking to ensure non-diagonal elements cannot be set.
 *
 * @author Keith Stevens 
 */
public class DiagonalMatrix extends AbstractMatrix
        implements SparseMatrix, java.io.Serializable {

    private static final long serialVersionUID = 1L;
        
    /**
     * The number diagonal values in this {@code Matrix}.
     */
    private double[] values;
    
    /**
     * Creates a new {@code DiagonalMatrix} with {@code numValues} rows and
     * columns.
     *
     * @param numValues The number of rows, columns, and diagonals in this
     *                  {@code DiagonalMatrix}.
     */
    public DiagonalMatrix(int numValues) {
        values = new double[numValues];
    }

    /**
     * Creates a new {@code DiagonalMatrix} with {@code newValues} as the
     * diagonal values.
     *
     * @param newValues The values to use as the diagonals of this {@code
     *                  Matrix}.
     */
    public DiagonalMatrix(double[] newValues) {
        values = new double[newValues.length];
        for (int i = 0; i < values.length; ++i)
            values[i] = newValues[i];
    }

    /**
     * Checks that the given row and column values are non-negative, and less
     * than the number of diagonals in this {@code DiagonalMatrix}.
     *
     * @param row The row index to check.
     * @param col The col index to check.
     *
     * @throws IllegalArgumentException if either index is invalid.
     */        
    private void checkIndices(int row, int col) {
        if (row < 0 || col < 0 || row >= values.length || col >= values.length)
            throw new ArrayIndexOutOfBoundsException();
    }

    /**
     * {@inheritDoc}
     */
    public double get(int row, int col) {
        checkIndices(row, col);

        if (row == col)
            return values[row];
        return 0;
    }

    /**
     * {@inheritDoc}
     */
    public double[] getColumn(int column) {
        checkIndices(0, column);

        double[] columnValues = new double[values.length];
        columnValues[column] = values[column];
        return columnValues;
    }

    /**
     * {@inheritDoc}
     */
    public SparseDoubleVector getColumnVector(int column) {
        checkIndices(0, column);
        SparseDoubleVector columnValues =
            new SparseHashDoubleVector(values.length);
        columnValues.set(column, values[column]);
        return columnValues;
    }

    /**
     * {@inheritDoc}
     */
    public double[] getRow(int row) {
        checkIndices(row, 0);

        double[] returnRow = new double[values.length];
        returnRow[row] = values[row];
        return returnRow;
    }

    /**
     * {@inheritDoc}
     */
    public SparseDoubleVector getRowVector(int row) {
        checkIndices(row, 0);
        SparseDoubleVector vector = new SparseHashDoubleVector(values.length);
        vector.set(row, values[row]);
        return vector;
    }

    /**
     * {@inheritDoc}
     */
    public int columns() {
        return values.length;
    }

    /**
     * {@inheritDoc}
     *
     * @throws IllegalArgumentException if {@code row != col}
     */
    public void set(int row, int col, double val) {
        checkIndices(row, col);

        if (row != col) {
            throw new IllegalArgumentException(
                    "cannot set non-diagonal elements in a DiagonalMatrix");
        }
        values[row] = val;
    }

    /**
     * {@inheritDoc}
     *
     * Note that any values are not on the diagonal are ignored.
     */
    public void setColumn(int column, double[] values) {
        checkIndices(values.length - 1, column);

        values[column] = values[column];
    }
    
    /**
     * {@inheritDoc}
     *
     * Note that any values are not on the diagonal are ignored.
     */
    public void setColumn(int column, DoubleVector vector) {
        checkIndices(vector.length() - 1, column);

        values[column] = vector.get(column);
    }

    /**
     * {@inheritDoc}
     *
     * Note that any values are not on the diagonal are ignored.
     */
    public void setRow(int row, double[] values) {
        checkIndices(row, values.length - 1);

        values[row] = values[row];
    }
    
    /**
     * {@inheritDoc}
     *
     * Note that any values are not on the diagonal are ignored.
     */
    public void setRow(int row, DoubleVector vector) {
        checkIndices(row, vector.length() - 1);

        values[row] = vector.get(row);
    }

    /**
     * {@inheritDoc}
     */
    public double[][] toDenseArray() {
        double[][] m = new double[values.length][values.length];
        for (int r = 0; r < values.length; ++r) {
            m[r][r] = values[r];
        }
        return m;
    }

    /**
     * {@inheritDoc}
     */
    public int rows() {
        return values.length;
    }
}