/**
* Returns KC distance between event sets es1 and es2
*
* @param es1 The first EventSet
* @param es2 The second EventSet
* @return the KC distance between them
*/
@Override
public double distance(EventSet es1, EventSet es2) {
EventHistogram h1 = es1.getHistogram();
EventHistogram h2 = es2.getHistogram();
Set<Event> s = new HashSet<Event>();
List<Pair<Event, Double>> l1 = new ArrayList<Pair<Event, Double>>();
List<Pair<Event, Double>> l2 = new ArrayList<Pair<Event, Double>>();
HashMap<Event, Integer> hm1 = new HashMap<Event, Integer>();
HashMap<Event, Integer> hm2 = new HashMap<Event, Integer>();
double oldfreq = Double.POSITIVE_INFINITY;
double correlation = 0.0;
s.addAll(es1.uniqueEvents());
s.addAll(es2.uniqueEvents());
// System.out.println(h1.toString());
// System.out.println(h2.toString());
/* make lists of the histograms */
for (Event e : h1) {
l1.add(new Pair<Event, Double>(e, h1.getRelativeFrequency(e), 2));
}
for (Event e : h2) {
l2.add(new Pair<Event, Double>(e, h2.getRelativeFrequency(e), 2));
}
/* sort the list so the most frequent items are at the top */
/* NOTE : THIS MAY BE USEFUL ELSEWHERE : SAVE THIS CODE */
Collections.sort(l1);
Collections.reverse(l1);
Collections.sort(l2);
Collections.reverse(l2);
/* DEBUGGING STUFF
for (Pair <Event,Double> p : l1) {
System.out.println("L1: " + p.toString());
}
for (Pair <Event,Double> p : l1) {
System.out.println("L2: " + p.toString());
}
*/
/* Convert lists into a hashmap of event:rank pairs */
int rank = 0;
int count = 0;
for (Pair<Event, Double> p : l1) {
Event e = (Event) (p.getFirst());
double f = (Double) (p.getSecond());
count++;
if (f != oldfreq) {
rank = count;
oldfreq = f;
}
hm1.put(e, rank);
}
/* reset and do second list */
rank = 0;
count = 0;
for (Pair<Event, Double> p : l2) {
Event e = (Event) (p.getFirst());
double f = (Double) (p.getSecond());
count++;
if (f != oldfreq) {
rank = count;
oldfreq = f;
}
hm2.put(e, rank);
}
/* More debugging stuff
System.out.println(hm1.toString());
System.out.println(hm2.toString());
System.out.println(s.toString());
*/
Integer x1, x2, y1, y2;
Set<Event> s2 = new HashSet<Event>(s);
for (Event e1 : s) {
// s2.remove(e1);
for (Event e2 : s2) {
if (e1.equals(e2)) continue;
/* get ranks of events e1 and e2 in both x and y distributions */
x1 = hm1.get(e1);
/* if not present, rank is size + 1 */
if (x1 == null) x1 = hm1.size() + 1;
x2 = hm2.get(e1);
if (x2 == null) x2 = hm2.size() + 1;
y1 = hm1.get(e2);
/* if not present, rank is size + 1 */
// broke because if (y1 == null) x1 = hm1.size()+1; x1 should be y1
if (y1 == null) y1 = hm1.size() + 1;
y2 = hm2.get(e2);
if (y2 == null) y2 = hm2.size() + 1;
/* more debugging stuff
System.out.println(e1.toString() + " is ("+x1+","+x2+")");
System.out.println(e2.toString() + " is ("+y1+","+y2+")");
System.out.println(sgn(x1.compareTo(y1)) + " " +
sgn(x2.compareTo(y2)) );
System.out.println("");
*/
correlation += (sgn(x1.compareTo(y1)) * sgn(x2.compareTo(y2)));
// System.out.println(correlation);
}
}
// System.out.println(correlation);
correlation /= (hm1.size() * (hm2.size() - 1));
// System.out.println(correlation);
// System.out.println("---");
return 1.0 - correlation;
}
