本文整理了Java中org.apache.commons.math3.stat.descriptive.moment.Mean.increment()方法的一些代码示例，展示了Mean.increment()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Mean.increment()方法的具体详情如下：
包路径：org.apache.commons.math3.stat.descriptive.moment.Mean
类名称：Mean
方法名：increment

Mean.increment介绍

[英]Note that when #Mean(FirstMoment) is used to create a Mean, this method does nothing. In that case, the FirstMoment should be incremented directly.
[中]请注意，当使用#Mean（FirstMoment）创建平均值时，此方法不起任何作用。在这种情况下，FirstMoment应该直接递增。

代码示例

代码示例来源：origin: org.apache.commons/commons-math3

/**
 * Add a new vector to the sample.
 * @param v vector to add
 * @throws DimensionMismatchException if the vector does not have the right dimension
 */
public void increment(double[] v) throws DimensionMismatchException {
  if (v.length != means.length) {
    throw new DimensionMismatchException(v.length, means.length);
  }
  for (int i = 0; i < v.length; ++i) {
    means[i].increment(v[i]);
  }
}

代码示例来源：origin: OryxProject/oryx

synchronized void recordTiming(long timeNanos) {
 meanTimeNanos.increment(timeNanos);
 stdevTimeNanos.increment(timeNanos);
}

代码示例来源：origin: OryxProject/oryx

@Test
public void testRecommendLoad() throws Exception {
 AtomicLong count = new AtomicLong();
 Mean meanReqTimeNanos = new Mean();
 long start = System.nanoTime();
 int workers = LoadTestALSModelFactory.WORKERS;
 ExecUtils.doInParallel(workers, workers, true, i -> {
  RandomGenerator random = RandomManager.getRandom(Integer.toString(i).hashCode() ^ System.nanoTime());
  for (int j = 0; j < LoadTestALSModelFactory.REQS_PER_WORKER; j++) {
   String userID = "U" + random.nextInt(LoadTestALSModelFactory.USERS);
   long callStart = System.nanoTime();
   target("/recommend/" + userID).request()
     .accept(MediaType.APPLICATION_JSON_TYPE).get(LIST_ID_VALUE_TYPE);
   long timeNanos = System.nanoTime() - callStart;
   if (j > 0) {
    // Ignore first iteration's time as 'burn in'
    synchronized (meanReqTimeNanos) {
     meanReqTimeNanos.increment(timeNanos);
    }
   }
   long currentCount = count.incrementAndGet();
   if (currentCount % 100 == 0) {
    log(currentCount, meanReqTimeNanos, start);
   }
  }
 });
 int totalRequests = workers * LoadTestALSModelFactory.REQS_PER_WORKER;
 log(totalRequests, meanReqTimeNanos, start);
}

代码示例来源：origin: lenskit/lenskit

private synchronized void addUser(double pop) {
    mean.increment(pop);
  }
}

代码示例来源：origin: lenskit/lenskit

synchronized void addUser(UserResult ur) {
    allMean.increment(ur.avgPrecision);
  }
}

代码示例来源：origin: apache/accumulo

public void addStat(long stat) {
 min = Math.min(min, stat);
 max = Math.max(max, stat);
 sum += stat;
 mean.increment(stat);
}

代码示例来源：origin: OryxProject/oryx

i++;
meanMatchLength.increment(i);
 i++;
meanMatchLength.increment(i);

代码示例来源：origin: lenskit/lenskit

@Nonnull
@Override
public MetricResult measureUserRecList(Recommender rec, TestUser user, int targetLength, List<Long> recommendations, Mean context) {
  int n = recommendations.size();
  synchronized (context) {
    context.increment(n);
  }
  return new LengthResult(n);
}

代码示例来源：origin: lenskit/lenskit

synchronized void addUser(UserResult ur) {
    allMean.increment(ur.getRecipRank());
  }
}

代码示例来源：origin: lenskit/lenskit

@Nonnull
@Override
public MetricResult measureUserRecList(Recommender rec, TestUser user, int targetLength, List<Long> recommendations, Mean context) {
  if (recommendations == null) {
    return MetricResult.empty();
  }
  Long2DoubleMap ratings = new Long2DoubleOpenHashMap();
  for (Entity e: user.getTestHistory()) {
    long item = e.getLong(CommonAttributes.ITEM_ID);
    Object av = e.get(gainAttribute);
    if (av instanceof Number) {
      ratings.put(item, ((Number) av).doubleValue());
    } else {
      throw new IllegalArgumentException("value " + av + " for attribute " + gainAttribute + " is not numeric");
    }
  }
  List<Long> ideal =
      ratings.keySet()
          .stream()
          .sorted(LongUtils.keyValueComparator(ratings).reversed())
          .limit(targetLength >= 0 ? targetLength : ratings.size())
          .collect(Collectors.toList());
  double idealGain = computeDCG(ideal, ratings);
  double gain = computeDCG(recommendations, ratings);
  double score = gain / idealGain;
  synchronized (context) {
    context.increment(score);
  }
  return MetricResult.singleton(columnName, score);
}

代码示例来源：origin: lenskit/lenskit

@Nonnull
@Override
public MetricResult measureUser(TestUser user, ResultMap predictions, Mean context) {
  if (predictions == null || predictions.isEmpty()) {
    return MetricResult.empty();
  }
  Long2DoubleMap ratings = user.getTestRatings();
  long[] ideal = ratings.keySet().toLongArray();
  LongArrays.quickSort(ideal, LongComparators.oppositeComparator(LongUtils.keyValueComparator(ratings)));
  long[] actual = LongUtils.asLongSet(predictions.keySet()).toLongArray();
  LongArrays.quickSort(actual, LongComparators.oppositeComparator(
      LongUtils.keyValueComparator(
          LongUtils.asLong2DoubleMap(predictions.scoreMap()))));
  double idealGain = computeDCG(ideal, ratings);
  double gain = computeDCG(actual, ratings);
  logger.debug("user {} has gain of {} (ideal {})", user.getUserId(), gain, idealGain);
  double score = gain / idealGain;
  synchronized (context) {
    context.increment(score);
  }
  ImmutableMap.Builder<String,Double> results = ImmutableMap.builder();
  return MetricResult.fromMap(results.put(columnName, score)
                    .put(columnName + ".Raw", gain)
                    .build());
}

代码示例来源：origin: meyerjp3/psychometrics

public void incrementMeanMean(Mean meanDiscrimination, Mean meanDifficulty){
  meanDiscrimination.increment(1.0);
  for(int i=0;i<ncatM1;i++){
    meanDifficulty.increment(difficulty-threshold[i]);
  }
}

代码示例来源：origin: meyerjp3/psychometrics

public void count(Object rowValue, Double itemScore){
  if(rowValue!=null && rowValue.equals(this.rowValue)){
    columns.addValue(itemScore);
    mean.increment(itemScore);
    rowTotal++;
  }
}

代码示例来源：origin: meyerjp3/psychometrics

/**
 * Mean/sigma linking coefficients are computed from the mean and standard deviation of item difficulty.
 * The summary statistics are computed in a storeless manner. This method allows for the incremental
 * update to item difficulty summary statistics by combining them with other summary statistics.
 *
 * @param mean item difficulty mean.
 * @param sd item difficulty standard deviation.
 */
public void incrementMeanSigma(Mean mean, StandardDeviation sd){//TODO check for correctness
  mean.increment(difficulty);
  sd.increment(difficulty);
}

代码示例来源：origin: hawkular/hawkular-metrics

public void increment(DataPoint<? extends Number> dataPoint) {
  Number value = dataPoint.getValue();
  min.increment(value.doubleValue());
  average.increment(value.doubleValue());
  max.increment(value.doubleValue());
  sum.increment(value.doubleValue());
  samples++;
  percentiles.stream().forEach(p -> p.addValue(value.doubleValue()));
}

代码示例来源：origin: org.hawkular.metrics/hawkular-metrics-core-service

public void increment(DataPoint<? extends Number> dataPoint) {
  Number value = dataPoint.getValue();
  min.increment(value.doubleValue());
  average.increment(value.doubleValue());
  max.increment(value.doubleValue());
  sum.increment(value.doubleValue());
  samples++;
  percentiles.stream().forEach(p -> p.addValue(value.doubleValue()));
}

代码示例来源：origin: org.hawkular.metrics/hawkular-metrics-core-service

public void increment(DataPoint<? extends Number> dataPoint) {
  Number value = dataPoint.getValue();
  min.increment(value.doubleValue());
  average.increment(value.doubleValue());
  max.increment(value.doubleValue());
  sum.increment(value.doubleValue());
  samples++;
  percentiles.stream().forEach(p -> p.addValue(value.doubleValue()));
}

代码示例来源：origin: jpmml/jpmml-evaluator

static
  private Double evaluate(Collection<?> values){
    Mean statistic = new Mean();

    for(Object value : values){
      Number number = (Number)TypeUtil.parseOrCast(DataType.DOUBLE, value);

      statistic.increment(number.doubleValue());
    }

    return statistic.getResult();
  }
}

代码示例来源：origin: org.jpmml/pmml-extension

static
  private Double evaluate(Collection<?> values){
    Mean statistic = new Mean();

    for(Object value : values){
      Double doubleValue = (Double)TypeUtil.parseOrCast(DataType.DOUBLE, value);

      statistic.increment(doubleValue.doubleValue());
    }

    return statistic.getResult();
  }
}

代码示例来源：origin: meyerjp3/psychometrics

public void increment(double score, String response, double freqWeight){
  Double d = Double.valueOf(score);
  TextItemResponseSummary irs = summaryTreeMap.get(d);
  if(null==irs){
    irs = new TextItemResponseSummary(variableName);
    summaryTreeMap.put(d, irs);
  }
  irs.increment(response, freqWeight);
  mean.increment(score);
  sd.increment(score);
  pearsonCorrelation.increment(score, irs.getScoreAt(response));
}