package com.jgaap.eventCullers;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import com.jgaap.generics.EventCullingException;
import com.jgaap.generics.FilterEventCuller;
import com.jgaap.util.Event;
import com.jgaap.util.EventHistogram;
import com.jgaap.util.EventSet;
import com.jgaap.util.Pair;
/**
* Analyze N events with highest weighted variance
* Var(x) = sum for i = 1 to n Pi*(xi-mean)^2
* where
* mean = sum for i = 1 to n Pi*xi"
*
* @author Christine Gray
*/
public class WeightedVariance extends FilterEventCuller {
public WeightedVariance() {
super();
addParams("numEvents", "N", "50", new String[] { "1", "2", "3", "4",
"5", "6", "7", "8", "9", "10", "15", "20", "25", "30", "40",
"45", "50", "75", "100", "150", "200" }, true);
addParams("Informative", "I", "Most", new String[] { "Most","Least"}, false);
}
@Override
public Set<Event> train(List<EventSet> eventSets)
throws EventCullingException {
int numEvents = getParameter("numEvents", 50);
String informative = getParameter("Informative", "Most");
EventHistogram hist = new EventHistogram();
for (EventSet oneSet : eventSets) {
for (Event e : oneSet) {
hist.add(e);
}
}
List<Pair<Event,Double>> WVar = new ArrayList<Pair<Event,Double>>();
List<EventHistogram> eventHistograms = new ArrayList<EventHistogram>(eventSets.size());
for (EventSet eventSet : eventSets) {
eventHistograms.add(new EventHistogram(eventSet));
}
for (Event event : hist) {
double mean = 0.0;
double var = 0.0;
double percentage = hist.getRelativeFrequency(event);
List<Integer> frequencies = new ArrayList<Integer>();
/*
* Calculate the mean
* sum i=1 to n Pi*xi
*/
for (EventHistogram eventHistogram : eventHistograms) {
int tmp = eventHistogram.getAbsoluteFrequency(event);
frequencies.add(tmp);
mean+= percentage*tmp;
}
/*
* Calculate the weighted variance
* Sum i=1 to n Pi(xi-mean)^2
*/
for(int i : frequencies){
var += percentage * Math.pow(i - mean, 2);
}
WVar.add(new Pair<Event, Double>(event, var, 2));
}
Collections.sort(WVar);
if(informative.equals("Most")){
Collections.reverse(WVar);
}
int counter = 0;
Set<Event> events = new HashSet<Event>(numEvents);
for(Pair<Event, Double> event : WVar){
counter++;
events.add(event.getFirst());
if(counter == numEvents)
break;
}
return events;
}
@Override
public String displayName() {
return "Weighted Variance";
}
@Override
public String tooltipText() {
return "Analyze N events with highest weighted variance";
}
@Override
public boolean showInGUI() {
return true;
}
@Override
public String longDescription(){
return "Analyze N events with highest weighted variance\n"+
"Var(x) = \u03A3 for i = 1 to n Pi*(xi-\u03BC)\u00B2\n"+
"where\n"+
"\u03BC = \u03A3 for i = 1 to n Pi*xi";
}
}