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The S-Space Package is a collection of algorithms for building Semantic Spaces as well as a highly-scalable library for designing new distributional semantics algorithms. Distributional algorithms process text corpora and represent the semantic for words as high dimensional feature vectors. This package also includes matrices, vectors, and numerous clustering algorithms. These approaches are known by many names, such as word spaces, semantic spaces, or distributed semantics and rest upon the Distributional Hypothesis: words that appear in similar contexts have similar meanings.

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/*
 * 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.vector;

import edu.ucla.sspace.util.DoubleEntry;

import java.io.Serializable;

import java.util.Arrays;


/**
 * A {@code Vector} where all values are held in memory. The underlying
 * implementation is simply an array of doubles.  
 *
 * @author Keith Stevens
*/
public class DenseVector extends AbstractDoubleVector
        implements Serializable {

    private static final long serialVersionUID = 1L;

    /**
     * The values of this {@code DenseVector}.
     */
    private double[] vector;

    /**
     * The magnitude of the vector or -1 if the value is currently invalid and
     * needs to be recomputed
     */
    private double magnitude;

    /**
     * Create an {@code DenseVector} with all values starting at 0 with
     * the given length.
     *
     * @param vectorLength The size of the vector to create.
     */
    public DenseVector(int vectorLength) {
        vector = new double[vectorLength];
        magnitude = 0;
    }

    /**
     * Create a {@code DenseVector} taking the values given by {@code vector}.
     * The created vector contains no references to the provided array, so
     * changes to either will not be reflected in the other.
     *
     * @param vector The vector values to start with.
     */
    public DenseVector(double[] vector) {
        this.vector = Arrays.copyOf(vector, vector.length);
        magnitude = -1;
    }
	
    /**
     * Create a {@code DenseVector} by copying the values from another {@code
     * Vector}.
     *
     * @param vector The {@code Vector} to copy from.
     */
    @SuppressWarnings("unchecked")
    public DenseVector(DoubleVector v) {
        this.vector = new double[v.length()];
        magnitude = v.magnitude();
        if (v instanceof Iterable) {
            for (DoubleEntry e : ((Iterable)v)) 
                vector[e.index()] = e.value();
        }
        else if (v instanceof SparseDoubleVector) {
            for (int i : ((SparseDoubleVector)v).getNonZeroIndices())
                vector[i] = v.get(i);
        }
        else {
            for (int i = 0; i < v.length(); ++i)
                vector[i] = v.get(i);
        }
    }

    /**
     * {@inheritDoc}
     */
    public double add(int index, double delta) {
        magnitude = -1;
        vector[index] += delta;
        return vector[index];
    }

    /**
     * {@inheritDoc}
     */
    public double get(int index) {
        return vector[index];
    }

    /**
     * {@inheritDoc}
     */
    public double magnitude() {
        if (magnitude < 0) {
            double m = 0;
            for (double d : vector)
                m += d * d;
            magnitude = Math.sqrt(m);
        }
        return magnitude;
    }

    /**
     * {@inheritDoc}
     */
    public void set(int index, double value) {
        magnitude = -1;
        vector[index] = value;
    }

    /**
     * {@inheritDoc}
     */
    public double[] toArray() {
        return Arrays.copyOf(vector, vector.length);
    }

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