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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 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 .
 */

package edu.ucla.sspace.matrix;

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

import java.io.BufferedInputStream;
import java.io.DataInputStream;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOError;
import java.io.IOException;
import java.io.RandomAccessFile;

import java.nio.ByteBuffer;

import java.nio.channels.FileChannel;
import java.nio.channels.FileChannel.MapMode;

import java.util.Iterator;
import java.util.NoSuchElementException;


/**
 * An iterator for sequentially accessing the rows of a {@link
 * MatrixIO.Format.SVDLIBC_SPARSE_BINARY} formatted file.
 *
 * @author David Jurgens
 */
class SvdlibcSparseBinaryFileRowIterator
    implements Iterator {

    /**
     * The stream of bytes in the matrix file.
     */
    private final ByteBuffer data;

    /**
     * The next {@link SparseDoubleVector} to be returned.
     */
    private SparseDoubleVector next;
    
    /**
     * The entry number that will next be returned from the matrix
     */
    private int entry;

    /**
     * The total number of non-zero entries in the matrix
     */
    private int nzEntriesInMatrix;

    /**
     * The index of the current column
     */
    private int curCol;

    /**
     * The number of rows in the matrix.
     */
    private final int rows;

    /**
     * The number of columns in the matrix.
     */
    private final int cols;

    /**
     * Creates a new {@link SvdlibcSparseBinaryFileRowIterator} for {@code
     * matrixFile}.
     */
    public SvdlibcSparseBinaryFileRowIterator(File matrixFile) 
            throws IOException {
        // Create the accessor for the data stream.
        RandomAccessFile raf = new RandomAccessFile(matrixFile, "r");
        FileChannel fc = raf.getChannel();
        data = fc.map(MapMode.READ_ONLY, 0, fc.size());
        fc.close();

        // Read the number of rows, columns, and non zero entries in the matrix.
        this.rows = data.getInt();
        this.cols = data.getInt();
        nzEntriesInMatrix = data.getInt();

        // Initialize the counters.
        curCol = 0;
        entry = 0;
        advance();
    }

    /**
     * Sets {@code next} to be the next row in the data matrix.
     */
    private void advance() throws IOException {        
        if (entry >= nzEntriesInMatrix) {
            next = null;
        }
        else {
            // Reads off a new vector from the data file.
            next = new SparseHashDoubleVector(rows);
            int nzInCol = data.getInt();
            for (int i = 0; i < nzInCol; ++i, ++entry) {
                int row = data.getInt();
                double value = data.getFloat();
                next.set(row, value);          
            }
            curCol++;
        }
    }

    /**
     * {@inheritDoc}
     */
    public boolean hasNext() {
        return next != null;
    }

    /**
     * {@inheritDoc}
     */
    public SparseDoubleVector next() {
        if (next == null) 
            throw new NoSuchElementException("No futher entries");

        SparseDoubleVector curCol = next;
        try {
            advance();
        } catch (IOException ioe) {
            throw new IOError(ioe);
        }
        return curCol;
    }

    /**
     * Throws an {@link UnsupportedOperationException} if called.
     */
    public void remove() {
        throw new UnsupportedOperationException("Cannot remove from file");
    }

    /**
     * Resets the iterator to the start of the file's data.
     */
    public void reset() {
        data.rewind();

        // Read off the rows, columns, and non-zero elements
        data.getInt();
        data.getInt();
        data.getInt();

        // Reset the counters.
        curCol = 0;
        entry = 0;
        try {
            advance();
        } catch (IOException ioe) {
            throw new IOError(ioe);
        }
    }
}