/*
* 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 2 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, write to the Free Software
* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
/*
* NearestNeighbourSearch.java
* Copyright (C) 1999-2007 University of Waikato
*/
package weka.core.neighboursearch;
import weka.core.AdditionalMeasureProducer;
import weka.core.DistanceFunction;
import weka.core.EuclideanDistance;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.Option;
import weka.core.OptionHandler;
import weka.core.RevisionHandler;
import weka.core.RevisionUtils;
import weka.core.Utils;
import java.io.Serializable;
import java.util.Enumeration;
import java.util.Vector;
/**
* Abstract class for nearest neighbour search. All algorithms (classes) that
* do nearest neighbour search should extend this class.
*
* @author Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
* @version $Revision: 1.2 $
*/
public abstract class NearestNeighbourSearch
implements Serializable, OptionHandler, AdditionalMeasureProducer,
RevisionHandler {
/**
* A class for a heap to store the nearest k neighbours to an instance.
* The heap also takes care of cases where multiple neighbours are the same
* distance away.
* i.e. the minimum size of the heap is k.
*
* @author Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
* @version $Revision: 1.2 $
*/
protected class MyHeap
implements RevisionHandler {
/** the heap. */
MyHeapElement m_heap[] = null;
/**
* constructor.
*
* @param maxSize the maximum size of the heap
*/
public MyHeap(int maxSize) {
if((maxSize%2)==0)
maxSize++;
m_heap = new MyHeapElement[maxSize+1];
m_heap[0] = new MyHeapElement(0, 0);
}
/**
* returns the size of the heap.
*
* @return the size
*/
public int size() {
return m_heap[0].index;
}
/**
* peeks at the first element.
*
* @return the first element
*/
public MyHeapElement peek() {
return m_heap[1];
}
/**
* returns the first element and removes it from the heap.
*
* @return the first element
* @throws Exception if no elements in heap
*/
public MyHeapElement get() throws Exception {
if(m_heap[0].index==0)
throw new Exception("No elements present in the heap");
MyHeapElement r = m_heap[1];
m_heap[1] = m_heap[m_heap[0].index];
m_heap[0].index--;
downheap();
return r;
}
/**
* adds the value to the heap.
*
* @param i the index
* @param d the distance
* @throws Exception if the heap gets too large
*/
public void put(int i, double d) throws Exception {
if((m_heap[0].index+1)>(m_heap.length-1))
throw new Exception("the number of elements cannot exceed the "+
"initially set maximum limit");
m_heap[0].index++;
m_heap[m_heap[0].index] = new MyHeapElement(i, d);
upheap();
}
/**
* Puts an element by substituting it in place of
* the top most element.
*
* @param i the index
* @param d the distance
* @throws Exception if distance is smaller than that of the head
* element
*/
public void putBySubstitute(int i, double d) throws Exception {
MyHeapElement head = get();
put(i, d);
// System.out.println("previous: "+head.distance+" current: "+m_heap[1].distance);
if(head.distance == m_heap[1].distance) { //Utils.eq(head.distance, m_heap[1].distance)) {
putKthNearest(head.index, head.distance);
}
else if(head.distance > m_heap[1].distance) { //Utils.gr(head.distance, m_heap[1].distance)) {
m_KthNearest = null;
m_KthNearestSize = 0;
initSize = 10;
}
else if(head.distance < m_heap[1].distance) {
throw new Exception("The substituted element is smaller than the "+
"head element. put() should have been called "+
"in place of putBySubstitute()");
}
}
/** the kth nearest ones. */
MyHeapElement m_KthNearest[] = null;
/** The number of kth nearest elements. */
int m_KthNearestSize = 0;
/** the initial size of the heap. */
int initSize=10;
/**
* returns the number of k nearest.
*
* @return the number of k nearest
* @see #m_KthNearestSize
*/
public int noOfKthNearest() {
return m_KthNearestSize;
}
/**
* Stores kth nearest elements (if there are
* more than one).
* @param i the index
* @param d the distance
*/
public void putKthNearest(int i, double d) {
if(m_KthNearest==null) {
m_KthNearest = new MyHeapElement[initSize];
}
if(m_KthNearestSize>=m_KthNearest.length) {
initSize += initSize;
MyHeapElement temp[] = new MyHeapElement[initSize];
System.arraycopy(m_KthNearest, 0, temp, 0, m_KthNearest.length);
m_KthNearest = temp;
}
m_KthNearest[m_KthNearestSize++] = new MyHeapElement(i, d);
}
/**
* returns the kth nearest element or null if none there.
*
* @return the kth nearest element
*/
public MyHeapElement getKthNearest() {
if(m_KthNearestSize==0)
return null;
m_KthNearestSize--;
return m_KthNearest[m_KthNearestSize];
}
/**
* performs upheap operation for the heap
* to maintian its properties.
*/
protected void upheap() {
int i = m_heap[0].index;
MyHeapElement temp;
while( i > 1 && m_heap[i].distance>m_heap[i/2].distance) {
temp = m_heap[i];
m_heap[i] = m_heap[i/2];
i = i/2;
m_heap[i] = temp; //this is i/2 done here to avoid another division.
}
}
/**
* performs downheap operation for the heap
* to maintian its properties.
*/
protected void downheap() {
int i = 1;
MyHeapElement temp;
while( ( (2*i) <= m_heap[0].index &&
m_heap[i].distance < m_heap[2*i].distance )
||
( (2*i+1) <= m_heap[0].index &&
m_heap[i].distance < m_heap[2*i+1].distance) ) {
if((2*i+1)<=m_heap[0].index) {
if(m_heap[2*i].distance>m_heap[2*i+1].distance) {
temp = m_heap[i];
m_heap[i] = m_heap[2*i];
i = 2*i;
m_heap[i] = temp;
}
else {
temp = m_heap[i];
m_heap[i] = m_heap[2*i+1];
i = 2*i+1;
m_heap[i] = temp;
}
}
else {
temp = m_heap[i];
m_heap[i] = m_heap[2*i];
i = 2*i;
m_heap[i] = temp;
}
}
}
/**
* returns the total size.
*
* @return the total size
*/
public int totalSize() {
return size()+noOfKthNearest();
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 1.2 $");
}
}
/**
* A class for storing data about a neighboring instance.
*
* @author Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
* @version $Revision: 1.2 $
*/
protected class MyHeapElement
implements RevisionHandler {
/** the index of this element. */
public int index;
/** the distance of this element. */
public double distance;
/**
* constructor.
*
* @param i the index
* @param d the distance
*/
public MyHeapElement(int i, double d) {
distance = d;
index = i;
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 1.2 $");
}
}
/**
* A class for storing data about a neighboring instance.
*
* @author Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
* @version $Revision: 1.2 $
*/ //better to change this into a heap element
protected class NeighborNode
implements RevisionHandler {
/** The neighbor instance. */
public Instance m_Instance;
/** The distance from the current instance to this neighbor. */
public double m_Distance;
/** A link to the next neighbor instance. */
public NeighborNode m_Next;
/**
* Create a new neighbor node.
*
* @param distance the distance to the neighbor
* @param instance the neighbor instance
* @param next the next neighbor node
*/
public NeighborNode(double distance, Instance instance, NeighborNode next) {
m_Distance = distance;
m_Instance = instance;
m_Next = next;
}
/**
* Create a new neighbor node that doesn't link to any other nodes.
*
* @param distance the distance to the neighbor
* @param instance the neighbor instance
*/
public NeighborNode(double distance, Instance instance) {
this(distance, instance, null);
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 1.2 $");
}
}
/**
* A class for a linked list to store the nearest k neighbours
* to an instance. We use a list so that we can take care of
* cases where multiple neighbours are the same distance away.
* i.e. the minimum length of the list is k.
*
* @author Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
* @version $Revision: 1.2 $
*/ //better to change this into a heap
protected class NeighborList
implements RevisionHandler {
/** The first node in the list. */
protected NeighborNode m_First;
/** The last node in the list. */
protected NeighborNode m_Last;
/** The number of nodes to attempt to maintain in the list. */
protected int m_Length = 1;
/**
* Creates the neighborlist with a desired length.
*
* @param length the length of list to attempt to maintain
*/
public NeighborList(int length) {
m_Length = length;
}
/**
* Gets whether the list is empty.
*
* @return true if list is empty
*/
public boolean isEmpty() {
return (m_First == null);
}
/**
* Gets the current length of the list.
*
* @return the current length of the list
*/
public int currentLength() {
int i = 0;
NeighborNode current = m_First;
while (current != null) {
i++;
current = current.m_Next;
}
return i;
}
/**
* Inserts an instance neighbor into the list, maintaining the list
* sorted by distance.
*
* @param distance the distance to the instance
* @param instance the neighboring instance
*/
public void insertSorted(double distance, Instance instance) {
if (isEmpty()) {
m_First = m_Last = new NeighborNode(distance, instance);
} else {
NeighborNode current = m_First;
if (distance < m_First.m_Distance) {// Insert at head
m_First = new NeighborNode(distance, instance, m_First);
} else { // Insert further down the list
for( ;(current.m_Next != null) &&
(current.m_Next.m_Distance < distance);
current = current.m_Next);
current.m_Next = new NeighborNode(distance, instance,
current.m_Next);
if (current.equals(m_Last)) {
m_Last = current.m_Next;
}
}
// Trip down the list until we've got k list elements (or more if the
// distance to the last elements is the same).
int valcount = 0;
for(current = m_First; current.m_Next != null;
current = current.m_Next) {
valcount++;
if ((valcount >= m_Length) && (current.m_Distance !=
current.m_Next.m_Distance)) {
m_Last = current;
current.m_Next = null;
break;
}
}
}
}
/**
* Prunes the list to contain the k nearest neighbors. If there are
* multiple neighbors at the k'th distance, all will be kept.
*
* @param k the number of neighbors to keep in the list.
*/
public void pruneToK(int k) {
if (isEmpty()) {
return;
}
if (k < 1) {
k = 1;
}
int currentK = 0;
double currentDist = m_First.m_Distance;
NeighborNode current = m_First;
for(; current.m_Next != null; current = current.m_Next) {
currentK++;
currentDist = current.m_Distance;
if ((currentK >= k) && (currentDist != current.m_Next.m_Distance)) {
m_Last = current;
current.m_Next = null;
break;
}
}
}
/**
* Prints out the contents of the neighborlist.
*/
public void printList() {
if (isEmpty()) {
System.out.println("Empty list");
} else {
NeighborNode current = m_First;
while (current != null) {
System.out.println("Node: instance " + current.m_Instance
+ ", distance " + current.m_Distance);
current = current.m_Next;
}
System.out.println();
}
}
/**
* returns the first element in the list.
*
* @return the first element
*/
public NeighborNode getFirst() {
return m_First;
}
/**
* returns the last element in the list.
*
* @return the last element
*/
public NeighborNode getLast() {
return m_Last;
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 1.2 $");
}
}
/** The neighbourhood of instances to find neighbours in. */
protected Instances m_Instances;
/** The number of neighbours to find. */
protected int m_kNN;
/** the distance function used. */
protected DistanceFunction m_DistanceFunction = new EuclideanDistance();
/** Performance statistics. */
protected PerformanceStats m_Stats = null;
/** Should we measure Performance. */
protected boolean m_MeasurePerformance = false;
/**
* Constructor.
*/
public NearestNeighbourSearch() {
if(m_MeasurePerformance)
m_Stats = new PerformanceStats();
}
/**
* Constructor.
*
* @param insts The set of instances that constitute the neighbourhood.
*/
public NearestNeighbourSearch(Instances insts) {
this();
m_Instances = insts;
}
/**
* Returns a string describing this nearest neighbour search algorithm.
*
* @return a description of the algorithm for displaying in the
* explorer/experimenter gui
*/
public String globalInfo() {
return
"Abstract class for nearest neighbour search. All algorithms (classes) that "
+ "do nearest neighbour search should extend this class.";
}
/**
* Returns an enumeration describing the available options.
*
* @return an enumeration of all the available options.
*/
public Enumeration listOptions() {
Vector newVector = new Vector();
newVector.add(new Option(
"\tDistance function to use.\n"
+ "\t(default: weka.core.EuclideanDistance)",
"A", 1,"-A <classname and options>"));
newVector.add(new Option(
"\tCalculate performance statistics.",
"P", 0,"-P"));
return newVector.elements();
}
/**
* Parses a given list of options. Valid options are:
*
<!-- options-start -->
<!-- options-end -->
*
* @param options the list of options as an array of strings
* @throws Exception if an option is not supported
*/
public void setOptions(String[] options) throws Exception {
String nnSearchClass = Utils.getOption('A', options);
if(nnSearchClass.length() != 0) {
String nnSearchClassSpec[] = Utils.splitOptions(nnSearchClass);
if(nnSearchClassSpec.length == 0) {
throw new Exception("Invalid DistanceFunction specification string.");
}
String className = nnSearchClassSpec[0];
nnSearchClassSpec[0] = "";
setDistanceFunction( (DistanceFunction)
Utils.forName( DistanceFunction.class,
className, nnSearchClassSpec) );
}
else {
setDistanceFunction(new EuclideanDistance());
}
setMeasurePerformance(Utils.getFlag('P',options));
}
/**
* Gets the current settings.
*
* @return an array of strings suitable for passing to setOptions()
*/
public String [] getOptions() {
Vector<String> result;
result = new Vector<String>();
result.add("-A");
result.add((m_DistanceFunction.getClass().getName() + " " +
Utils.joinOptions(m_DistanceFunction.getOptions())).trim());
if(getMeasurePerformance())
result.add("-P");
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 distanceFunctionTipText() {
return "The distance function to use for finding neighbours " +
"(default: weka.core.EuclideanDistance). ";
}
/**
* returns the distance function currently in use.
*
* @return the distance function
*/
public DistanceFunction getDistanceFunction() {
return m_DistanceFunction;
}
/**
* sets the distance function to use for nearest neighbour search.
*
* @param df the new distance function to use
* @throws Exception if instances cannot be processed
*/
public void setDistanceFunction(DistanceFunction df) throws Exception {
m_DistanceFunction = df;
}
/**
* Returns the tip text for this property.
*
* @return tip text for this property suitable for
* displaying in the explorer/experimenter gui
*/
public String measurePerformanceTipText() {
return "Whether to calculate performance statistics " +
"for the NN search or not";
}
/**
* Gets whether performance statistics are being calculated or not.
*
* @return true if the measure performance is calculated
*/
public boolean getMeasurePerformance() {
return m_MeasurePerformance;
}
/**
* Sets whether to calculate the performance statistics or not.
*
* @param measurePerformance if true then the performance is calculated
*/
public void setMeasurePerformance(boolean measurePerformance) {
m_MeasurePerformance = measurePerformance;
if(m_MeasurePerformance) {
if(m_Stats==null)
m_Stats = new PerformanceStats();
}
else
m_Stats = null;
}
/**
* Returns the nearest instance in the current neighbourhood to the supplied
* instance.
*
* @param target The instance to find the nearest neighbour for.
* @return the nearest neighbor
* @throws Exception if the nearest neighbour could not be found.
*/
public abstract Instance nearestNeighbour(Instance target) throws Exception;
/**
* Returns k nearest instances in the current neighbourhood to the supplied
* instance.
*
* @param target The instance to find the k nearest neighbours for.
* @param k The number of nearest neighbours to find.
* @return the k nearest neighbors
* @throws Exception if the neighbours could not be found.
*/
public abstract Instances kNearestNeighbours(Instance target, int k) throws Exception;
/**
* Returns the distances of the k nearest neighbours. The kNearestNeighbours
* or nearestNeighbour needs to be called first for this to work.
*
* @return the distances
* @throws Exception if called before calling kNearestNeighbours
* or nearestNeighbours.
*/
public abstract double[] getDistances() throws Exception;
/**
* Updates the NearNeighbourSearch algorithm for the new added instance.
* P.S.: The method assumes the instance has already been added to the
* m_Instances object by the caller.
*
* @param ins the instance to add
* @throws Exception if updating fails
*/
public abstract void update(Instance ins) throws Exception;
/**
* Adds information from the given instance without modifying the
* datastructure a lot.
*
* @param ins the instance to add the information from
*/
public void addInstanceInfo(Instance ins) {
}
/**
* Sets the instances.
*
* @param insts the instances to use
* @throws Exception if setting fails
*/
public void setInstances(Instances insts) throws Exception {
m_Instances = insts;
}
/**
* returns the instances currently set.
*
* @return the current instances
*/
public Instances getInstances() {
return m_Instances;
}
/**
* Gets the class object that contains the performance statistics of
* the search method.
*
* @return the performance statistics
*/
public PerformanceStats getPerformanceStats() {
return m_Stats;
}
/**
* Returns an enumeration of the additional measure names.
*
* @return an enumeration of the measure names
*/
public Enumeration enumerateMeasures() {
Vector newVector;
if(m_Stats == null) {
newVector = new Vector(0);
}
else {
newVector = new Vector();
Enumeration en = m_Stats.enumerateMeasures();
while(en.hasMoreElements())
newVector.add(en.nextElement());
}
return newVector.elements();
}
/**
* Returns the value of the named measure.
*
* @param additionalMeasureName the name of the measure to query for
* its value
* @return the value of the named measure
* @throws IllegalArgumentException if the named measure is not supported
*/
public double getMeasure(String additionalMeasureName) {
if(m_Stats==null)
throw new IllegalArgumentException(additionalMeasureName
+ " not supported (NearestNeighbourSearch)");
else
return m_Stats.getMeasure(additionalMeasureName);
}
/**
* sorts the two given arrays.
*
* @param arrayToSort The array sorting should be based on.
* @param linkedArray The array that should have the same ordering as
* arrayToSort.
*/
public static void combSort11(double arrayToSort[], int linkedArray[]) {
int switches, j, top, gap;
double hold1; int hold2;
gap = arrayToSort.length;
do {
gap=(int)(gap/1.3);
switch(gap) {
case 0:
gap = 1;
break;
case 9:
case 10:
gap=11;
break;
default:
break;
}
switches=0;
top = arrayToSort.length-gap;
for(int i=0; i<top; i++) {
j=i+gap;
if(arrayToSort[i] > arrayToSort[j]) {
hold1=arrayToSort[i];
hold2=linkedArray[i];
arrayToSort[i]=arrayToSort[j];
linkedArray[i]=linkedArray[j];
arrayToSort[j]=hold1;
linkedArray[j]=hold2;
switches++;
}//endif
}//endfor
} while(switches>0 || gap>1);
}
/**
* Partitions the instances around a pivot. Used by quicksort and
* kthSmallestValue.
*
* @param arrayToSort the array of doubles to be sorted
* @param linkedArray the linked array
* @param l the first index of the subset
* @param r the last index of the subset
* @return the index of the middle element
*/
protected static int partition(double[] arrayToSort, double[] linkedArray, int l, int r) {
double pivot = arrayToSort[(l + r) / 2];
double help;
while (l < r) {
while ((arrayToSort[l] < pivot) && (l < r)) {
l++;
}
while ((arrayToSort[r] > pivot) && (l < r)) {
r--;
}
if (l < r) {
help = arrayToSort[l];
arrayToSort[l] = arrayToSort[r];
arrayToSort[r] = help;
help = linkedArray[l];
linkedArray[l] = linkedArray[r];
linkedArray[r] = help;
l++;
r--;
}
}
if ((l == r) && (arrayToSort[r] > pivot)) {
r--;
}
return r;
}
/**
* performs quicksort.
*
* @param arrayToSort the array to sort
* @param linkedArray the linked array
* @param left the first index of the subset
* @param right the last index of the subset
*/
public static void quickSort(double[] arrayToSort, double[] linkedArray, int left, int right) {
if (left < right) {
int middle = partition(arrayToSort, linkedArray, left, right);
quickSort(arrayToSort, linkedArray, left, middle);
quickSort(arrayToSort, linkedArray, middle + 1, right);
}
}
}