package tclass.clusteralg; import tclass.*; public class GClustVec implements ClusterVecI {    EventDescI eventDesc;     GClust[] clusters;     float[] sds;     int pepIndex;     int numParams;     float[][] clustSDs;     int distMetric;    EventI[] origEvents;         public GClustVec(EventDescI eventDesc, int numClusters, float[] sds, int pepIndex, float[][] clustSDs, int distMetric, EventI[] origEvents){        this.eventDesc = eventDesc;         numParams = eventDesc.numParams();         clusters = new GClust[numClusters];         this.sds = sds;         this.pepIndex = pepIndex;         this.clustSDs = clustSDs;         this.distMetric = distMetric;         this.origEvents = origEvents;     }        public void insert(GClust clus, int position){        clusters[position] = clus;     }        public int size(){        return clusters.length;     }        public Object clone()    {        try {            return super.clone();         }        catch (CloneNotSupportedException e){            // Can't happen, or so the java programming book says            throw new InternalError(e.toString());         }    }        public ClusterI elAt(int i){        return clusters[i];     }    // This is just bullshit. Ignore this.     public ClusterMem findBestLabel(EventI event){        float[] distances = getDistances(event);         int[] best = smallestTwo(distances);         float confidence;         if(distMetric == GainCluster.DISTRATIO){            confidence = (float) Math.log(distances[best[1]]/distances[best[0]]);                    }        else {            confidence = (float) 1/distances[best[0]]; // 1/ to cause it to be the same way.          }        ClusterMem retval = new ClusterMem(clusters[best[0]], confidence);         retval.setOrigEvent(event);         return retval;            }        public float findMatch(int cluster, StreamEventsI sei){        // First pull out the events of interest:         EventVecI events = sei.getEvents(pepIndex);         int numEvents = events.size();         float currMatch;         // To get the confidence we need the most popular and second most popular.         float bestMatch = -Float.MAX_VALUE;         for(int i=0; i < numEvents; i++){            float[] distances = getDistances(events.elAt(i));             int[] best = smallestTwo(distances);             if(best[0] == cluster){                // In other words, it's a match.                 if(distMetric == GainCluster.DISTRATIO){                    currMatch = distances[best[1]]/distances[best[0]];                 }                else {                    currMatch = 1/distances[best[0]];                 }                if(currMatch > bestMatch){                    bestMatch = currMatch;                 }            }        }        if(bestMatch == -Float.MAX_VALUE){            return 0;         }        else {            return (float) Math.log(bestMatch);         }    }            public float[] getDistances(EventI ev){        float[] retval = new float[clusters.length];         for(int i=0; i < clusters.length; i++){            retval[i] = distance(clusters[i].cent(), ev);         }        return retval;     }    float distance(EventI ev1, EventI ev2){        float retval;         float sumDist2=0;         for(int i=0; i < numParams; i++){            float rawDist = (ev1.valOf(i)-ev2.valOf(i))/sds[i];             sumDist2 += rawDist*rawDist;         }        retval = (float) Math.sqrt(sumDist2);        return retval;     }    // Finds the index of the smallest and second smallest instances in the given array.     int[] smallestTwo(float[] data){        // Assumes we have at least two elements         int smallest, secondSmallest;         if(data[0] > data[1]){             smallest = 1;             secondSmallest = 0;         }        else {            smallest = 0;             secondSmallest = 1;         }        for(int i=2; i < data.length; i++){            if(data[i] < data[secondSmallest]){                if(data[i] < data[smallest]){                    secondSmallest = smallest;                     smallest = i;                 }                else {                    secondSmallest = i;                 }            }        }        int[] retval = new int[2];         retval[0] = smallest;         retval[1] = secondSmallest;         return retval;     }}