Example usage for java.util Collections min

Introduction

In this page you can find the example usage for java.util Collections min.

Prototype

public static <T extends Object & Comparable<? super T>> T min(Collection<? extends T> coll) 

Source Link

Document

Returns the minimum element of the given collection, according to the natural ordering of its elements.

Usage

From source file:org.spotter.ext.detection.highmessaging.analyze.LogAnalyzer.java

@Override
public AnalyzeResult analyze() {
    result.addMessage("*************************************************");
    result.addMessage("Testing data for stagnating progression..");

    TrendLine logTrend = new LogTrendLine();
    logTrend.setValues(toDoubleArray(normalize(yValues, Collections.min(yValues))), toDoubleArray(xValues));

    List<Double> smoothed = smooth(yValues, SMOOTH_WIDE);

    SimpleRegression first = new SimpleRegression();
    first.addData(/*from  www  .j av a  2  s .c o m*/
            toDoubleArray(subList(xValues, 0, xValues.size() / 2), subList(smoothed, 0, xValues.size() / 2)));

    SimpleRegression second = new SimpleRegression();
    second.addData(toDoubleArray(subList(xValues, xValues.size() / 2), subList(smoothed, xValues.size() / 2)));

    result.addMessage("> Slope 0%-50%:   " + first.getSlope());
    result.addMessage("> Slope 50%-100%: " + second.getSlope());
    result.addMessage("> Threshold:      " + maxSlopeFactor * first.getSlope());

    if (Math.abs(second.getSlope()) < maxSlopeFactor * first.getSlope()) {
        result.addMessage("> detected");
        return AnalyzeResult.POSITIVE;
    } else {
        result.addMessage("> not detected");
        return AnalyzeResult.NEGATIVE;
    }
}

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From source file:org.apache.lens.cube.parse.LightestFactResolver.java

@Override
public void rewriteContext(CubeQueryContext cubeql) throws SemanticException {
    if (cubeql.getCube() != null && !cubeql.getCandidateFactSets().isEmpty()) {
        Map<Set<CandidateFact>, Double> factWeightMap = new HashMap<Set<CandidateFact>, Double>();

        for (Set<CandidateFact> facts : cubeql.getCandidateFactSets()) {
            factWeightMap.put(facts, getWeight(facts));
        }//from   w  w  w.  ja v  a2s .  c  o m

        double minWeight = Collections.min(factWeightMap.values());

        for (Iterator<Set<CandidateFact>> i = cubeql.getCandidateFactSets().iterator(); i.hasNext();) {
            Set<CandidateFact> facts = i.next();
            if (factWeightMap.get(facts) > minWeight) {
                LOG.info("Not considering facts:" + facts
                        + " from candidate fact tables as it has more fact weight:" + factWeightMap.get(facts)
                        + " minimum:" + minWeight);
                i.remove();
            }
        }
        cubeql.pruneCandidateFactWithCandidateSet(CandidateTablePruneCode.MORE_WEIGHT);
    }
}

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From source file:org.apache.lens.cube.parse.LeastPartitionResolver.java

@Override
public void rewriteContext(CubeQueryContext cubeql) throws SemanticException {
    if (cubeql.getCube() != null && !cubeql.getCandidateFactSets().isEmpty()) {
        Map<Set<CandidateFact>, Integer> factPartCount = new HashMap<Set<CandidateFact>, Integer>();

        for (Set<CandidateFact> facts : cubeql.getCandidateFactSets()) {
            factPartCount.put(facts, getPartCount(facts));
        }//from   www  . java2 s .c  o m

        double minPartitions = Collections.min(factPartCount.values());

        for (Iterator<Set<CandidateFact>> i = cubeql.getCandidateFactSets().iterator(); i.hasNext();) {
            Set<CandidateFact> facts = i.next();
            if (factPartCount.get(facts) > minPartitions) {
                LOG.info("Not considering facts:" + facts
                        + " from candidate fact tables as it requires more partitions to" + " be queried:"
                        + factPartCount.get(facts) + " minimum:" + minPartitions);
                i.remove();
            }
        }
        cubeql.pruneCandidateFactWithCandidateSet(CandidateTablePruneCode.MORE_PARTITIONS);
    }
}

---

From source file:org.opensourcebank.batch.partition.HazelcastMapPartitioner.java

public Map<String, ExecutionContext> partition(int gridSize) {

    Map<Long, Object> itemsMap = Hazelcast.getMap(mapName);
    Set<Long> itemsIds = itemsMap.keySet();

    long min = 0;
    long max = 0;

    if (itemsIds.size() > 0) {
        min = Collections.min(itemsIds);
        max = Collections.max(itemsIds);
    }/*www  . j a v a2 s  . c om*/

    long targetSize = (max - min) / gridSize + 1;

    Map<String, ExecutionContext> result = new HashMap<String, ExecutionContext>();
    int number = 0;
    long start = min;
    long end = start + targetSize - 1;

    while (start <= max) {

        ExecutionContext value = new ExecutionContext();
        result.put("partition" + number, value);

        if (end >= max) {
            end = max;
        }
        value.putLong("fromId", start);
        value.putLong("toId", end);
        value.putString("mapName", mapName);
        start += targetSize;
        end += targetSize;
        number++;
    }

    return result;
}

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From source file:org.zkoss.ganttz.data.GanttDate.java

public static GanttDate min(GanttDate... dates) {
    return Collections.min(Arrays.asList(dates));
}

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From source file:com.yimidida.shards.strategy.exit.impl.AggregateExitOperation.java

@Override
public List<Object> apply(List<Object> result) {
    if (result.size() == 0) {
        return Lists.newArrayList((Object) 0);
    }//from   ww  w. ja  v  a  2  s.c om

    //      String className = result.get(0).getClass().getName();

    List<Object> nonNullResults = ExitOperationUtils.getNonNullList(result);

    switch (aggregate) {
    case MAX:
        return Collections
                .<Object>singletonList(Collections.max(ExitOperationUtils.getComparableList(nonNullResults)));
    case MIN:
        return Collections
                .<Object>singletonList(Collections.min(ExitOperationUtils.getComparableList(nonNullResults)));
    case SUM:
        return Collections.<Object>singletonList(getSum(nonNullResults, null).intValue());
    default:
        log.error("Aggregation Projection is unsupported: " + aggregate);
        throw new UnsupportedOperationException("Aggregation Projection is unsupported: " + aggregate);
    }
}

---

From source file:org.apache.hadoop.mapreduce.lib.partition.TestRehashPartitioner.java

/** test partitioner for patterns */
@Test/*from   www. j ava 2 s. c o  m*/
public void testPatterns() {
    int results[] = new int[PARTITIONS];
    RehashPartitioner<IntWritable, NullWritable> p = new RehashPartitioner<IntWritable, NullWritable>();
    /* test sequence 4, 8, 12, ... 128 */
    for (int i = 0; i < END; i += STEP) {
        results[p.getPartition(new IntWritable(i), null, PARTITIONS)]++;
    }
    int badbuckets = 0;
    Integer min = Collections.min(Arrays.asList(ArrayUtils.toObject(results)));
    Integer max = Collections.max(Arrays.asList(ArrayUtils.toObject(results)));
    Integer avg = (int) Math.round((max + min) / 2.0);
    System.out.println("Dumping buckets distribution: min=" + min + " avg=" + avg + " max=" + max);
    for (int i = 0; i < PARTITIONS; i++) {
        double var = (results[i] - avg) / (double) (avg);
        System.out.println("bucket " + i + " " + results[i] + " items, variance " + var);
        if (Math.abs(var) > MAX_ERROR)
            badbuckets++;
    }
    System.out.println(badbuckets + " of " + PARTITIONS + " are too small or large buckets");
    assertTrue("too many overflow buckets", badbuckets < PARTITIONS * MAX_BADBUCKETS);
}

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From source file:org.wallerlab.yoink.molecular.service.calculator.ClosestDistanceToMoleculeCalculator.java

/**
 * calculate the distance minimum between a coordinate and a molecule.
 * /*from ww  w .  ja  v a2 s  .c o  m*/
 * @param gridCoord
 *            -{@link org.wallerlab.yoink.api.model.molecular.Coord}
 * @param molecule
 *            -{@link org.wallerlab.yoink.api.model.molecular.Molecule}
 * @return density -{@link java.lang.Double}
 * 
 */
public Double calculate(Coord gridCoord, Molecule molecule) {
    List<Double> distances = new ArrayList<Double>();
    for (Atom atom : molecule.getAtoms()) {
        double tempdistance = distanceCalculator.calculate(gridCoord, atom);
        distances.add(tempdistance);
    }
    double distance = Collections.min(distances);
    return distance;
}

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From source file:org.mrgeo.aggregators.MinAvgPairAggregator.java

@Override
public double aggregate(double[] values, double nodata) {
    boolean data0 = Double.compare(values[0], nodata) != 0;
    boolean data1 = Double.compare(values[1], nodata) != 0;
    boolean data2 = Double.compare(values[2], nodata) != 0;
    boolean data3 = Double.compare(values[3], nodata) != 0;

    Collection<Double> averages = new ArrayList<Double>();
    if (data0 && data1)
        averages.add(Double.valueOf((values[0] + values[1]) / 2));
    if (data0 && data2)
        averages.add(Double.valueOf((values[0] + values[2]) / 2));
    if (data0 && data3)
        averages.add(Double.valueOf((values[0] + values[3]) / 2));
    if (data1 && data2)
        averages.add(Double.valueOf((values[1] + values[2]) / 2));
    if (data1 && data3)
        averages.add(Double.valueOf((values[1] + values[3]) / 2));
    if (data2 && data3)
        averages.add(Double.valueOf((values[2] + values[3]) / 2));

    return (averages.isEmpty()) ? nodata : Collections.min(averages).doubleValue();
}

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From source file:org.apache.lens.cube.parse.LightestDimensionResolver.java

@Override
public void rewriteContext(CubeQueryContext cubeql) throws SemanticException {
    if (!cubeql.getCandidateDimTables().isEmpty()) {
        for (Map.Entry<Dimension, Set<CandidateDim>> entry : cubeql.getCandidateDimTables().entrySet()) {
            if (entry.getValue().isEmpty()) {
                continue;
            }/*from   w w  w  .ja  v a2s.  c o  m*/
            Map<CandidateDim, Double> dimWeightMap = new HashMap<CandidateDim, Double>();

            for (CandidateDim dim : entry.getValue()) {
                dimWeightMap.put(dim, dim.dimtable.weight());
            }

            double minWeight = Collections.min(dimWeightMap.values());

            for (Iterator<CandidateDim> i = entry.getValue().iterator(); i.hasNext();) {
                CandidateDim dim = i.next();
                if (dimWeightMap.get(dim) > minWeight) {
                    LOG.info("Not considering dimtable:" + dim
                            + " from candidate dimension tables as it has more weight:" + dimWeightMap.get(dim)
                            + " minimum:" + minWeight);
                    cubeql.addDimPruningMsgs(entry.getKey(), dim.dimtable,
                            new CandidateTablePruneCause(CandidateTablePruneCode.MORE_WEIGHT));
                    i.remove();
                }
            }
        }
    }
}

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