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MLVector.java

gehe zur Dokumentation dieser Datei

/*
 * $Source: /shared/cvsroot/diplom/app/src/java/de/picana/clusterer/MLVector.java,v $
 * $Author: mstolpe $
 * $Date: 2003/04/22 09:51:28 $
 * $Revision: 1.6 $
 * $Release$
 *
 * Created on 20. November 2002, 23:38
 *
 * Copyright 2002 by Marco Stolpe
 */

package de.picana.clusterer;

import java.text.*;
import java.util.*;

import weka.core.*;


public class MLVector implements Comparable {
    
    private static final DecimalFormat df;
    private static Random rand = new Random();
    
    static {
        df = (DecimalFormat)DecimalFormat.getInstance(Locale.ENGLISH);
        df.applyPattern("####0.000000");
    }
    
    public double[] value;
    public int dim;
    public int freq;
    public boolean pruned;
    public boolean visited;
    
    public MLVector(int dim) {
        this.value = new double[dim];
        this.freq = 0;
        this.pruned = false;
        this.visited = false;
        this.dim = dim;
    }
    
    public MLVector(Instance inst) {
        this.value = new double[inst.numAttributes()];
        this.freq = 1;
        this.pruned = false;
        this.visited = false;
        this.dim = inst.numAttributes();
        for (int i=0; i < dim; i++) {
            this.value[i] = inst.value(i); 
        }
    }
    
    public boolean equals(Object o) {
        if (!(o instanceof MLVector))
            return false;

        MLVector vec = (MLVector)o;

        if (vec.dim != this.dim)
            return false;
        
        boolean eq = true;
        
        int i = 0;
        while ((i < vec.dim) && (eq != false)) {
            if (vec.value[i] != this.value[i])
                eq = false;
            i++;    
        }
        
        return eq;
    }
    
    public int hashCode() {
        double sum = 0.0;
        int i;
        for (i=0; i < dim; i++)
            sum += value[i];
        return (int)(sum * 100000 / dim);
    }
    
    public int compareTo(Object o) {
        MLVector vec = (MLVector)o;

        if (vec.dim != this.dim)
            return -1;
        
        int i = 0;
        while (i < vec.dim) {
            if (this.value[i] < vec.value[i])
                return -1;
            else if (this.value[i] > vec.value[i])
                return 1;
            i++;
        }
        
        return 0;
    }
    
    public void mult(double scalar) {
        for (int i=0; i < value.length; i++) {
            value[i] *= scalar;
        }
    }
    
    public void add(MLVector vec) {
        for (int i=0; i < value.length; i++) {
            value[i] += vec.value[i];    
        }    
    }
    
    public void sub(MLVector vec) {
        for (int i=0; i < value.length; i++) {
            value[i] -= vec.value[i];    
        }
    }
    
    public static MLVector sub(MLVector vec1, MLVector vec2) {
        MLVector vec = new MLVector(vec1.dim);
        for (int i=0; i < vec.dim; i++) {
            vec.value[i] = vec1.value[i] - vec2.value[i];    
        }
        return vec;
    }
    
    public static MLVector getRandom(MLVector src, double radius) {
        MLVector vec = new MLVector(src.dim);
        for (int i=0; i < src.dim; i++) {
            vec.value[i] = src.value[i] + (radius - rand.nextDouble() * (radius * 2));
            if (vec.value[i] < 0) vec.value[i] = 0.0;
            if (vec.value[i] > 1.0) vec.value[i] = 1.0;
        }
        return vec;
    }
    
    public String toString() {
        int i;
        String str = "(";
        for (i=0; i < dim; i++) {
            str += value[i]; // df.format(value[i]);
            if (i != dim-1)
                str += ", ";
        }
        str += ") -> ";
        str += this.freq;
        return str;
    }
}

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