Java tutorial
/* * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. */ /* * MinkowskiDistance.java * Copyright (C) 2009-2012 University of Waikato, Hamilton, New Zealand * */ package weka.core; import java.util.Collections; import java.util.Enumeration; import java.util.Vector; import weka.core.TechnicalInformation.Field; import weka.core.TechnicalInformation.Type; import weka.core.neighboursearch.PerformanceStats; /** * <!-- globalinfo-start --> Implementing Minkowski distance (or similarity) * function.<br/> * <br/> * One object defines not one distance but the data model in which the distances * between objects of that data model can be computed.<br/> * <br/> * Attention: For efficiency reasons the use of consistency checks (like are the * data models of the two instances exactly the same), is low.<br/> * <br/> * For more information, see:<br/> * <br/> * Wikipedia. Minkowski distance. URL * http://en.wikipedia.org/wiki/Minkowski_distance. * <p/> * <!-- globalinfo-end --> * * <!-- technical-bibtex-start --> BibTeX: * * <pre> * @misc{missing_id, * author = {Wikipedia}, * title = {Minkowski distance}, * URL = {http://en.wikipedia.org/wiki/Minkowski_distance} * } * </pre> * <p/> * <!-- technical-bibtex-end --> * * <!-- options-start --> Valid options are: * <p/> * * <pre> * -P <order> * The order 'p'. With '1' being the Manhattan distance and '2' * the Euclidean distance. * (default: 2) * </pre> * * <pre> * -D * Turns off the normalization of attribute * values in distance calculation. * </pre> * * <pre> * -R <col1,col2-col4,...> * Specifies list of columns to used in the calculation of the * distance. 'first' and 'last' are valid indices. * (default: first-last) * </pre> * * <pre> * -V * Invert matching sense of column indices. * </pre> * * <!-- options-end --> * * @author FracPete (fracpete at waikato dot ac dot nz) * @version $Revision$ */ public class MinkowskiDistance extends NormalizableDistance implements Cloneable, TechnicalInformationHandler { /** for serialization. */ private static final long serialVersionUID = -7446019339455453893L; /** the order of the minkowski distance. */ protected double m_Order = 2; /** * Constructs an Minkowski Distance object, Instances must be still set. */ public MinkowskiDistance() { super(); } /** * Constructs an Minkowski Distance object and automatically initializes the * ranges. * * @param data the instances the distance function should work on */ public MinkowskiDistance(Instances data) { super(data); } /** * Returns a string describing this object. * * @return a description of the evaluator suitable for displaying in the * explorer/experimenter gui */ @Override public String globalInfo() { return "Implementing Minkowski distance (or similarity) function.\n\n" + "One object defines not one distance but the data model in which " + "the distances between objects of that data model can be computed.\n\n" + "Attention: For efficiency reasons the use of consistency checks " + "(like are the data models of the two instances exactly the same), " + "is low.\n\n" + "For more information, see:\n\n" + getTechnicalInformation().toString(); } /** * Returns an instance of a TechnicalInformation object, containing detailed * information about the technical background of this class, e.g., paper * reference or book this class is based on. * * @return the technical information about this class */ @Override public TechnicalInformation getTechnicalInformation() { TechnicalInformation result; result = new TechnicalInformation(Type.MISC); result.setValue(Field.AUTHOR, "Wikipedia"); result.setValue(Field.TITLE, "Minkowski distance"); result.setValue(Field.URL, "http://en.wikipedia.org/wiki/Minkowski_distance"); return result; } /** * Returns an enumeration describing the available options. * * @return an enumeration of all the available options. */ @Override public Enumeration<Option> listOptions() { Vector<Option> result = new Vector<Option>(); result.addElement(new Option("\tThe order 'p'. With '1' being the Manhattan distance and '2'\n" + "\tthe Euclidean distance.\n" + "\t(default: 2)", "P", 1, "-P <order>")); result.addAll(Collections.list(super.listOptions())); return result.elements(); } /** * Parses a given list of options. * * @param options the list of options as an array of strings * @throws Exception if an option is not supported */ @Override public void setOptions(String[] options) throws Exception { String tmpStr; tmpStr = Utils.getOption('P', options); if (tmpStr.length() > 0) { setOrder(Double.parseDouble(tmpStr)); } else { setOrder(2); } super.setOptions(options); } /** * Gets the current settings of this object. * * @return an array of strings suitable for passing to setOptions */ @Override public String[] getOptions() { Vector<String> result; result = new Vector<String>(); result.add("-P"); result.add("" + getOrder()); Collections.addAll(result, super.getOptions()); return result.toArray(new String[result.size()]); } /** * Returns the tip text for this property. * * @return tip text for this property suitable for displaying in the * explorer/experimenter gui */ public String orderTipText() { return "The order of the Minkowski distance ('1' is Manhattan distance and " + "'2' the Euclidean distance)."; } /** * Sets the order. * * @param value the new order */ public void setOrder(double value) { if (m_Order != 0.0) { m_Order = value; invalidate(); } else { System.err.println("Order cannot be zero!"); } } /** * Gets the order. * * @return the order */ public double getOrder() { return m_Order; } /** * Calculates the distance between two instances. * * @param first the first instance * @param second the second instance * @return the distance between the two given instances */ @Override public double distance(Instance first, Instance second) { return Math.pow(distance(first, second, Double.POSITIVE_INFINITY), 1 / m_Order); } /** * Calculates the distance (or similarity) between two instances. Need to pass * this returned distance later on to postprocess method to set it on correct * scale. <br/> * P.S.: Please don't mix the use of this function with distance(Instance * first, Instance second), as that already does post processing. Please * consider passing Double.POSITIVE_INFINITY as the cutOffValue to this * function and then later on do the post processing on all the distances. * * @param first the first instance * @param second the second instance * @param stats the structure for storing performance statistics. * @return the distance between the two given instances or * Double.POSITIVE_INFINITY. */ @Override public double distance(Instance first, Instance second, PerformanceStats stats) { // debug // method // pls // remove // after // use return Math.pow(distance(first, second, Double.POSITIVE_INFINITY, stats), 1 / m_Order); } /** * Updates the current distance calculated so far with the new difference * between two attributes. The difference between the attributes was * calculated with the difference(int,double,double) method. * * @param currDist the current distance calculated so far * @param diff the difference between two new attributes * @return the update distance * @see #difference(int, double, double) */ @Override protected double updateDistance(double currDist, double diff) { double result; result = currDist; result += Math.pow(Math.abs(diff), m_Order); return result; } /** * Does post processing of the distances (if necessary) returned by * distance(distance(Instance first, Instance second, double cutOffValue). It * is necessary to do so to get the correct distances if * distance(distance(Instance first, Instance second, double cutOffValue) is * used. This is because that function actually returns the squared distance * to avoid inaccuracies arising from floating point comparison. * * @param distances the distances to post-process */ @Override public void postProcessDistances(double distances[]) { for (int i = 0; i < distances.length; i++) { distances[i] = Math.pow(distances[i], 1 / m_Order); } } /** * Returns the revision string. * * @return the revision */ @Override public String getRevision() { return RevisionUtils.extract("$Revision: 0$"); } }