Examples of AdaptiveHistogram

com.flaptor.hist4j.AdaptiveHistogram
This class implements a histogram that adapts to an unknown data distribution. It keeps a more or less constant resolution throughout the data range by increasing the resolution where the data is more dense. For example, if the data has such such a distribution that most of the values lie in the 0-5 range and only a few are in the 5-10 range, the histogram would adapt and assign more counting buckets to the 0-5 range and less to the 5-10 range. This implementation provides a method to obtain the accumulative density function for a given data point, and a method to obtain the data point that splits the data set at a given percentile. @author Jorge Handl

Examples of com.flaptor.hist4j.AdaptiveHistogram

        NodeDescriptor node = cluster.getNodes().get(Integer.parseInt(request.getParameter("id")));
        String eventName = request.getParameter("eventName");
        MonitorModule monitor = (MonitorModule)cluster.getModule("monitor");
        MonitorNodeDescriptor mnode = monitor.getModuleNode(node);
        Statistics statistics = (Statistics)mnode.getLastState().getProperties().get("statistics");
        AdaptiveHistogram hist = statistics.getLastPeriodStats(eventName).getHistogram();
        Calendar c = DateUtil.getCanonicalDayFromToday(0);
        
        Map<Date, List<Number>> ret = new HashMap<Date, List<Number>>(); 
        float last = 0;
        for (int i = 0; i<100; i += 10) {
            float value = hist.getValueForPercentile(i) - last; 
            last = hist.getValueForPercentile(i);
            List<Number> numbers = new ArrayList<Number>();
            numbers.add(last);
            numbers.add(last);
            ret.put(c.getTime(), numbers);
            c = DateUtil.getCanonicalDayFrom(c, 1);

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Examples of com.flaptor.hist4j.AdaptiveHistogram

        cycleCount = 0;
        failedPages = 0;
        fetchedPages = 0;
        fetchedScore = 0;
        initialized = true;
        priorityHistogram = new AdaptiveHistogram();
        scoreHistogram = new AdaptiveHistogram();
        antiScoreHistogram = new AdaptiveHistogram();
    }

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Examples of com.flaptor.hist4j.AdaptiveHistogram

        } else {
            pageCount = 0;
            failedPages = 0;
            fetchedPages = 0;
            fetchedScore = 0;
            priorityHistogram = new AdaptiveHistogram();
            scoreHistogram = new AdaptiveHistogram();
            antiScoreHistogram = new AdaptiveHistogram();
        }
        try {
            pageSource.open();
            while (true) {
                Page page = pageSource.nextPage();

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Examples of com.flaptor.hist4j.AdaptiveHistogram

        pagedb = new ArrayList<Page>();
        for (int i = 0; i < maxPages; i++) {
            Page page = new Page(i);
            pagedb.add(page);
        }
        histogram = new AdaptiveHistogram();
pagedb.get(0).probSuccess = 0.0f;
pagedb.get(0).probChange = 1.0f;
    }

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Examples of com.flaptor.hist4j.AdaptiveHistogram

        public LuceneIterator() {
            seen = 0;
            try {
                int terms = 0;
                maxFreq = 0;
                AdaptiveHistogram hist = new AdaptiveHistogram();
                termEnum = reader.terms(new Term(field,""));


                while (termEnum.next()) {
                    hist.addValue(termEnum.docFreq());
                    terms++;
                    maxFreq = Math.max(maxFreq,termEnum.docFreq());
                }


                threshold = (int)hist.getValueForPercentile(90);


                termEnum = reader.terms(new Term(field,""));
            } catch (IOException e) {
                throw new RuntimeException(e);
            }

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Examples of com.flaptor.hist4j.AdaptiveHistogram


public class Hist4jExample {


    public static void main(String[] args) {
        Random rnd = new Random(new Date().getTime());
        AdaptiveHistogram h = new AdaptiveHistogram();


        System.out.println();
        System.out.println("Loading 10000 Gauss(0,1) data points into the histogram.");
        
        for (int i=0; i < 10000; i ++) {
            h.addValue((float)rnd.nextGaussian());
        }


        System.out.println();
        System.out.println("Main percentiles:");
        System.out.println("   5%: " + h.getValueForPercentile(5));
        System.out.println("  25%: " + h.getValueForPercentile(25));
        System.out.println("  50%: " + h.getValueForPercentile(50));
        System.out.println("  75%: " + h.getValueForPercentile(75));
        System.out.println("  95%: " + h.getValueForPercentile(95));
        System.out.println();
        System.out.println("Cumulative density:");
        for (float x=-1; x<=1; x+=0.5) {
            System.out.println("  " + x + ": " + h.getAccumCount(x));
        }
        System.out.println();
    }

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