Package edu.ucla.sspace.mains

Source Code of edu.ucla.sspace.mains.LpcsMain

/*
* 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 <http://www.gnu.org/licenses/>.
*/

package edu.ucla.sspace.mains;

import edu.ucla.sspace.common.ArgOptions;
import edu.ucla.sspace.common.SemanticSpace;
import edu.ucla.sspace.common.SemanticSpaceIO.SSpaceFormat;

import edu.ucla.sspace.matrix.AffinityMatrixCreator;

import edu.ucla.sspace.nonlinear.LocalityPreservingCooccurrenceSpace;

import edu.ucla.sspace.similarity.CosineSimilarity;
import edu.ucla.sspace.similarity.SimilarityFunction;

import edu.ucla.sspace.util.ReflectionUtil;

import java.io.IOError;
import java.io.IOException;

import java.util.Properties;


/**
* An executable class for running {@link LocalityPreservingCooccurrenceSpace}
* (LPWS) from the command line.
*
* <p>
*
* An invocation will produce one file as output {@code lpcs.sspace}.  If {@code
* overwrite} was set to {@code true}, this file will be replaced for each new
* semantic space.  Otherwise, a new output file of the format {@code
* lpsa-semantic-space<number>.sspace} will be created, where {@code <number>}
* is a unique identifier for that program's invocation.  The output file will
* be placed in the directory specified on the command line.
*
* <p>
*
* This class is desgined to run multi-threaded and performs well with one
* thread per core, which is the default setting.
*
* @see LocalityPreservingCooccurrenceSpace
* @see edu.ucla.sspace.matrix.Transform Transform
*
* @author David Jurgens
*/
public class LpcsMain extends GenericMain {

    private LpcsMain() { }

    /**
     * Adds all of the options to the {@link ArgOptions}.
     */
    protected void addExtraOptions(ArgOptions options) {
        options.addOption('n', "dimensions",
                          "the number of dimensions in the semantic space",
                          true, "INT", "Algorithm Options");
        options.addOption('e', "edgeType",
                          "the AffinityMatrixCreator that will select " +
                          "edges for an affinity matrix",
                          true, "CLASSNAME", "Required");
        options.addOption('E', "edgeSimParam",
                          "a parameter that the edge selection method may use.",
                          true, "DOUBLE", "Algorithm Options");
        options.addOption('W', "kernelSim",
                          "the SimilarityFunction for weighting edges in " +
                          "the affinity matrix",
                          true, "CLASSNAME", "Required");
        options.addOption('G', "edgeWeightingParam",
                          "a parameter that the kernelSim method may use.",
                          true, "DOUBLE", "Algorithm Options");
        options.addOption('s', "windowSize",
                          "The number of words to inspect to the left and " +
                          "right of a focus word (default: 5)",
                          true, "INT", "Algorithm Options");
    }

    public static void main(String[] args) {
        LpcsMain lpsa = new LpcsMain();
        try {
            lpsa.run(args);
        }
        catch (Throwable t) {
            t.printStackTrace();
        }
    }
   
    protected SemanticSpace getSpace() {
        AffinityMatrixCreator creator = ReflectionUtil.getObjectInstance(
                argOptions.getStringOption('e'));
        if (argOptions.hasOption("edgeTypeParam"))
            creator.setParams(argOptions.getIntOption("edgeTypeParam"));

        SimilarityFunction edgeSim = new CosineSimilarity();
        SimilarityFunction kernelSim = ReflectionUtil.getObjectInstance(
                argOptions.getStringOption("edgeWeighting"));
        if (argOptions.hasOption("edgeWeighting"))
            kernelSim.setParams(argOptions.getIntOption("edgeWeightingParam"));
        creator.setFunctions(edgeSim, kernelSim);

        return new LocalityPreservingCooccurrenceSpace(creator);
    }

    /**
     * Returns the {@likn SSpaceFormat.BINARY binary} format as the default
     * format of a {@code LocalityPreservingCooccurrenceSpace} space.
     */
    protected SSpaceFormat getSpaceFormat() {
        return SSpaceFormat.BINARY;
    }

    protected Properties setupProperties() {
        // use the System properties in case the user specified them as
        // -Dprop=<val> to the JVM directly.
        Properties props = System.getProperties();
        if (argOptions.hasOption("windowSize")) {
            props.setProperty(
                LocalityPreservingCooccurrenceSpace.WINDOW_SIZE_PROPERTY,
                argOptions.getStringOption("windowSize"));
        }
        return props;
    }

    /**
     * {@inheritDoc}
     */
    protected String getAlgorithmSpecifics() {
        return "The --edgeType option specifies the method by which words are "+
            "connected in\n" +
            "the affinity matrix.  Two options are provided: " +
            "NEAREST_NEIGHBORS and\n" +
            "MIN_SIMILARITY.  Each takes a parameter specified by the " +
            "--edgeTypeParam\n" +
            "option.  For NEAREST_NEIGHBORS, the parameter specifies how " +
            "many words will\n" +
            "be counted as edges in the affinity matrix.  For MIN_SIMILARITY, "+
            "the parameter\n" +
            "specifies the minimum similarity for two words to have an " +
            "edge.\n\n" +
           
            "The --edgeWeighting option specifies how edges in the affinity " +
            "matrix should\n" +
            "be weighted.  Valid options are: BINARY, GAUSSIAN_KERNEL, " +
            "POLYNOMIAL_KERNEL,\n" +
            "DOT_PRODUCT, COSINE_SIMILARITY.  The Gaussian and polynomial " +
            "kernels take an\n" +
            "optional parameter specified by --edgeWeightingParam that " +
            "weights the kernel\n" +
            "function.  The other options ignore the value of the " +
            "parameter.\n\n" +

            "The default behavior is the use NEAREST_NEIGHBORS with a value " +
            "of 20 and\n" +
            "COSINE_SIMILARITY edge weighting.";
    }
}
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