本文整理了Java中java.util.stream.Stream.mapToDouble()方法的一些代码示例，展示了Stream.mapToDouble()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。Stream.mapToDouble()方法的具体详情如下：
包路径：java.util.stream.Stream
类名称：Stream
方法名：mapToDouble

Stream.mapToDouble介绍

[英]Returns a DoubleStream consisting of the results of applying the given function to the elements of this stream.

This is an intermediate operation.
[中]返回一个DoubleStream，其中包含将给定函数应用于该流元素的结果。
这是一个intermediate operation。

代码示例

代码示例来源：origin: prestodb/presto

public Optional<IndexInfo> build()
  {
    List<Integer> partitions = partitionsSizes.build();
    if (partitions.size() == 0) {
      return Optional.empty();
    }
    double avgSize = partitions.stream().mapToLong(Integer::longValue).average().getAsDouble();
    double squaredDifferences = partitions.stream().mapToDouble(size -> Math.pow(size - avgSize, 2)).sum();
    checkState(partitions.stream().mapToLong(Integer::longValue).sum() == rowsNumber, "Total number of rows in index does not match number of rows in partitions within that index");
    return Optional.of(new IndexInfo(rowsNumber, sizeInBytes, squaredDifferences, partitions.size()));
  }
}

代码示例来源：origin: apache/storm

private double fragmentedMemory() {
  Double res = nodeIdToResources.get().values().parallelStream().filter(this::isFragmented)
                 .mapToDouble(SupervisorResources::getAvailableMem).filter(x -> x > 0).sum();
  return res.intValue();
}

代码示例来源：origin: apache/storm

private int fragmentedCpu() {
  Double res = nodeIdToResources.get().values().parallelStream().filter(this::isFragmented)
                 .mapToDouble(SupervisorResources::getAvailableCpu).filter(x -> x > 0).sum();
  return res.intValue();
}

代码示例来源：origin: stanfordnlp/CoreNLP

private void trainPolicy(List<List<Pair<CandidateAction, CandidateAction>>> examples) {
 List<Pair<CandidateAction, CandidateAction>> flattenedExamples = new ArrayList<>();
 examples.stream().forEach(flattenedExamples::addAll);
 for (int epoch = 0; epoch < NUM_EPOCHS; epoch++) {
  Collections.shuffle(flattenedExamples, random);
  flattenedExamples.forEach(classifier::learn);
 }
 double totalCost = flattenedExamples.stream()
   .mapToDouble(e -> classifier.bestAction(e).cost).sum();
 Redwood.log("scoref.train",
   String.format("Training cost: %.4f", 100 * totalCost / flattenedExamples.size()));
}

代码示例来源：origin: google/error-prone

double totalAssignmentCost() {
 return assignmentCost().stream().mapToDouble(d -> d).sum();
}

代码示例来源：origin: google/error-prone

double totalOriginalCost() {
 return originalCost().stream().mapToDouble(d -> d).sum();
}

代码示例来源：origin: apache/incubator-druid

@Override
public RelOptCost computeSelfCost(final RelOptPlanner planner, final RelMetadataQuery mq)
{
 return planner.getCostFactory().makeCost(rels.stream().mapToDouble(mq::getRowCount).sum(), 0, 0);
}

代码示例来源：origin: confluentinc/ksql

public static double aggregateStat(final String name, final boolean isError) {
 return collectorMap.values().stream()
   .mapToDouble(m -> m.aggregateStat(name, isError))
   .sum();
}

代码示例来源：origin: stanfordnlp/CoreNLP

public static double[] pairwiseScoreThresholds(Properties props) {
 String thresholdsProp = props.getProperty("coref.statistical.pairwiseScoreThresholds");
 if (thresholdsProp != null) {
  String[] split = thresholdsProp.split(",");
  if (split.length == 4) {
   return Arrays.stream(split).mapToDouble(Double::parseDouble).toArray();
  }
 }
 double threshold = PropertiesUtils.getDouble(
   props, "coref.statistical.pairwiseScoreThresholds", 0.35);
 return new double[] {threshold, threshold, threshold, threshold};
}

代码示例来源：origin: apache/storm

@Override
  protected Double transform(ClusterSummary clusterSummary) {
    return clusterSummary.get_supervisors().stream()
        //Filtered negative value
        .mapToDouble(supervisorSummary -> Math.max(supervisorSummary.get_fragmented_mem(), 0))
        .sum();
  }
});

代码示例来源：origin: apache/storm

@Override
  protected Double transform(ClusterSummary clusterSummary) {
    return clusterSummary.get_supervisors().stream()
        //Filtered negative value
        .mapToDouble(supervisorSummary -> Math.max(supervisorSummary.get_fragmented_cpu(), 0))
        .sum();
  }
});

代码示例来源：origin: prestodb/presto

/**
 * Returns estimated data size.
 * Unknown value is represented by {@link Double#NaN}
 */
public double getOutputSizeInBytes(Collection<Symbol> outputSymbols, TypeProvider types)
{
  requireNonNull(outputSymbols, "outputSymbols is null");
  return outputSymbols.stream()
      .mapToDouble(symbol -> getOutputSizeForSymbol(getSymbolStatistics(symbol), types.get(symbol)))
      .sum();
}

代码示例来源：origin: apache/storm

private static double getCpuUsed(SchedulerAssignment assignment) {
  return assignment.getScheduledResources().values().stream().mapToDouble((wr) -> wr.get_cpu()).sum();
}

代码示例来源：origin: confluentinc/ksql

public static <T> double aggregateStat(
  final String name,
  final boolean isError,
  final Collection<TopicSensors<T>> sensors) {
 return sensors.stream()
   .flatMap(r -> r.stats(isError).stream())
   .filter(s -> s.name().equals(name))
   .mapToDouble(TopicSensors.Stat::getValue)
   .sum();
}

代码示例来源：origin: prestodb/presto

private int getNewTaskCount()
{
  if (scheduledNodes.isEmpty()) {
    return 1;
  }
  double fullTasks = sourceTasksProvider.get().stream()
      .filter(task -> !task.getState().isDone())
      .map(TaskStatus::isOutputBufferOverutilized)
      .mapToDouble(full -> full ? 1.0 : 0.0)
      .average().orElse(0.0);
  long writtenBytes = writerTasksProvider.get().stream()
      .map(TaskStatus::getPhysicalWrittenDataSize)
      .mapToLong(DataSize::toBytes)
      .sum();
  if ((fullTasks >= 0.5) && (writtenBytes >= (writerMinSizeBytes * scheduledNodes.size()))) {
    return 1;
  }
  return 0;
}

代码示例来源：origin: apache/storm

private static double getMemoryUsed(SchedulerAssignment assignment) {
  return assignment.getScheduledResources().values().stream()
           .mapToDouble((wr) -> wr.get_mem_on_heap() + wr.get_mem_off_heap()).sum();
}

代码示例来源：origin: prestodb/presto

@VisibleForTesting
static double calculateNullsFractionForPartitioningKey(
    HiveColumnHandle column,
    List<HivePartition> partitions,
    Map<String, PartitionStatistics> statistics,
    double averageRowsPerPartition,
    double rowCount)
{
  if (rowCount == 0) {
    return 0;
  }
  double estimatedNullsCount = partitions.stream()
      .filter(partition -> partition.getKeys().get(column).isNull())
      .map(HivePartition::getPartitionId)
      .mapToDouble(partitionName -> getPartitionRowCount(partitionName, statistics).orElse(averageRowsPerPartition))
      .sum();
  return normalizeFraction(estimatedNullsCount / rowCount);
}

代码示例来源：origin: apache/ignite

/**
   * Creates {@link VectorGenerator} with vectors having feature values in according to
   * preudorandom producers.
   *
   * @param producers Feature value producers.
   * @return Vector generator.
   */
  public static VectorGenerator vectorize(RandomProducer... producers) {
    A.notEmpty(producers, "producers");

    return () -> VectorUtils.of(Arrays.stream(producers).mapToDouble(Supplier::get).toArray());
  }
}

代码示例来源：origin: apache/ignite

/** {@inheritDoc} */
  @Override public Vector get() {
    Double t = randomProducer.get();
    return VectorUtils.of(perDimensionGenerators.stream()
      .mapToDouble(f -> f.apply(t)).toArray());
  }
}

代码示例来源：origin: neo4j/neo4j

private static double[] coordinatesAsArray( JsonNode element )
{
  return Iterables.stream( element.get( "coordinates" ) )
      .mapToDouble( JsonNode::asDouble )
      .toArray();
}