/** {@inheritDoc} */ @Override public Double apply(double[] estimations) { A.notEmpty(estimations, "estimations vector"); return Arrays.stream(estimations).reduce(0.0, Double::sum) / estimations.length; } }
default OptionalDouble reduce(DoublePipeline pipeline, DoubleBinaryOperator op) { requireNonNull(pipeline); requireNonNull(op); return optimize(pipeline).getAsDoubleStream().reduce(op); }
default double reduce(DoublePipeline pipeline, double identity, DoubleBinaryOperator op) { requireNonNull(pipeline); requireNonNull(identity); requireNonNull(op); return optimize(pipeline).getAsDoubleStream().reduce(identity, op); }
@Override public double reduce(double identity, DoubleBinaryOperator op) { return finallyClose(() -> stream().reduce(identity, op)); }
@Override public OptionalDouble reduce(DoubleBinaryOperator op) { return finallyClose(() -> stream().reduce(op)); }
return ((Iterator<BigDecimal>) iter).foldLeft(((BigDecimal) o), BigDecimal::multiply); } else { return ((Iterator<Number>) iter).toJavaStream().mapToDouble(Number::doubleValue).reduce(((Number) o).doubleValue(), (d1, d2) -> d1 * d2);
@Override public double reduce(double zeroValue, @NonNull SerializableDoubleBinaryOperator operator) { return stream.reduce(zeroValue, operator); }
@Override public OptionalDouble reduce(@NonNull SerializableDoubleBinaryOperator operator) { return stream.reduce(operator); }
public double getMaxValue() { return mySeries.stream().mapToDouble(Series::getMaxValue).reduce(0.0D, Math::max); } }
private double estimatedGroupCount(List<Symbol> symbols, PlanNodeStatsEstimate statsEstimate) { return symbols.stream() .map(statsEstimate::getSymbolStatistics) .mapToDouble(this::ndvIncludingNull) // This assumes no correlation, maximum number of aggregation keys .reduce(1, (a, b) -> a * b); }
/** * Utility method to calculate the probability that all cardinality estimates are correct. * * @param estimates some {@link CardinalityEstimate}s * @return the joint probability of all {@link CardinalityEstimate}s being correct */ private double calculateJointProbability(CardinalityEstimate[] estimates) { return Arrays.stream(estimates) .map(this::replaceNullCardinality) .mapToDouble(CardinalityEstimate::getCorrectnessProbability) .reduce(1d, (a, b) -> a * b); }
@Override public OptionalDouble reduce(final DoubleBinaryOperator op) { // This is a terminal operation return evalAndclose(() -> stream.reduce(op)); }
@Override public double reduce(final double identity, final DoubleBinaryOperator op) { // This is a terminal operation return evalAndclose(() -> stream.reduce(identity, op)); }
default double reduce(DoublePipeline pipeline, double identity, DoubleBinaryOperator op) { requireNonNull(pipeline); requireNonNull(identity); requireNonNull(op); return optimize(pipeline).getAsDoubleStream().reduce(identity, op); }
default OptionalDouble reduce(DoublePipeline pipeline, DoubleBinaryOperator op) { requireNonNull(pipeline); requireNonNull(op); return optimize(pipeline).getAsDoubleStream().reduce(op); }
@Override public double reduce(double identity, DoubleBinaryOperator op) { return finallyClose(() -> stream().reduce(identity, op)); }
/** * Gets volume. * * @return the volume */ public double getVolume() { int dim = min.length; return IntStream.range(0, dim).mapToDouble(d -> { return max[d] - min[d]; }).filter(x -> Double.isFinite(x) && x > 0.0).reduce((a, b) -> a * b).orElse(Double.NaN); }
@Override public OptionalDouble reduce(DoubleBinaryOperator op) { if (context.fjp != null) return context.terminate(op, stream()::reduce); return stream().reduce(op); }