The following example illustrates an aggregate operation using * {@link Stream} and {@link DoubleStream}, computing the sum of the weights of the * red widgets: * *
{@code
* double sum = widgets.stream()
* .filter(w -> w.getColor() == RED)
* .mapToDouble(w -> w.getWeight())
* .sum();
* }
*
* See the class documentation for {@link Stream} and the package documentation
* for java.util.stream for additional
* specification of streams, stream operations, stream pipelines, and
* parallelism.
*
* @since 1.8
* @see Stream
* @see java.util.stream
*/
public interface DoubleStream extends BaseStreamThis is an intermediate * operation. * * @param predicate a non-interfering, * stateless * predicate to apply to each element to determine if it * should be included * @return the new stream */ DoubleStream filter(DoublePredicate predicate); /** * Returns a stream consisting of the results of applying the given * function to the elements of this stream. * *
This is an intermediate * operation. * * @param mapper a non-interfering, * stateless * function to apply to each element * @return the new stream */ DoubleStream map(DoubleUnaryOperator mapper); /** * Returns an object-valued {@code Stream} consisting of the results of * applying the given function to the elements of this stream. * *
This is an * intermediate operation. * * @param the element type of the new stream * @param mapper a non-interfering, * stateless * function to apply to each element * @return the new stream */ Stream mapToObj(DoubleFunction mapper); /** * Returns an {@code IntStream} consisting of the results of applying the * given function to the elements of this stream. * *
This is an intermediate * operation. * * @param mapper a non-interfering, * stateless * function to apply to each element * @return the new stream */ IntStream mapToInt(DoubleToIntFunction mapper); /** * Returns a {@code LongStream} consisting of the results of applying the * given function to the elements of this stream. * *
This is an intermediate * operation. * * @param mapper a non-interfering, * stateless * function to apply to each element * @return the new stream */ LongStream mapToLong(DoubleToLongFunction mapper); /** * Returns a stream consisting of the results of replacing each element of * this stream with the contents of a mapped stream produced by applying * the provided mapping function to each element. Each mapped stream is * {@link java.util.stream.BaseStream#close() closed} after its contents * have been placed into this stream. (If a mapped stream is {@code null} * an empty stream is used, instead.) * *
This is an intermediate * operation. * * @param mapper a non-interfering, * stateless * function to apply to each element which produces a * {@code DoubleStream} of new values * @return the new stream * @see Stream#flatMap(Function) */ DoubleStream flatMap(DoubleFunction mapper); /** * Returns a stream consisting of the results of replacing each element of * this stream with multiple elements, specifically zero or more elements. * Replacement is performed by applying the provided mapping function to each * element in conjunction with a {@linkplain DoubleConsumer consumer} argument * that accepts replacement elements. The mapping function calls the consumer * zero or more times to provide the replacement elements. * *
This is an intermediate * operation. * *
If the {@linkplain DoubleConsumer consumer} argument is used outside the scope of * its application to the mapping function, the results are undefined. * * @implSpec * The default implementation invokes {@link #flatMap flatMap} on this stream, * passing a function that behaves as follows. First, it calls the mapper function * with a {@code DoubleConsumer} that accumulates replacement elements into a newly created * internal buffer. When the mapper function returns, it creates a {@code DoubleStream} from the * internal buffer. Finally, it returns this stream to {@code flatMap}. * * @param mapper a non-interfering, * stateless * function that generates replacement elements * @return the new stream * @see Stream#mapMulti Stream.mapMulti * @since 16 */ default DoubleStream mapMulti(DoubleMapMultiConsumer mapper) { Objects.requireNonNull(mapper); return flatMap(e -> { SpinedBuffer.OfDouble buffer = new SpinedBuffer.OfDouble(); mapper.accept(e, buffer); return StreamSupport.doubleStream(buffer.spliterator(), false); }); } /** * Returns a stream consisting of the distinct elements of this stream. The * elements are compared for equality according to * {@link java.lang.Double#compare(double, double)}. * *
This is a stateful * intermediate operation. * * @return the result stream */ DoubleStream distinct(); /** * Returns a stream consisting of the elements of this stream in sorted * order. The elements are compared for equality according to * {@link java.lang.Double#compare(double, double)}. * *
This is a stateful * intermediate operation. * * @return the result stream */ DoubleStream sorted(); /** * Returns a stream consisting of the elements of this stream, additionally * performing the provided action on each element as elements are consumed * from the resulting stream. * *
This is an intermediate * operation. * *
For parallel stream pipelines, the action may be called at * whatever time and in whatever thread the element is made available by the * upstream operation. If the action modifies shared state, * it is responsible for providing the required synchronization. * * @apiNote This method exists mainly to support debugging, where you want * to see the elements as they flow past a certain point in a pipeline: *
{@code
* DoubleStream.of(1, 2, 3, 4)
* .filter(e -> e > 2)
* .peek(e -> System.out.println("Filtered value: " + e))
* .map(e -> e * e)
* .peek(e -> System.out.println("Mapped value: " + e))
* .sum();
* }
*
* In cases where the stream implementation is able to optimize away the * production of some or all the elements (such as with short-circuiting * operations like {@code findFirst}, or in the example described in * {@link #count}), the action will not be invoked for those elements. * * @param action a * non-interfering action to perform on the elements as * they are consumed from the stream * @return the new stream */ DoubleStream peek(DoubleConsumer action); /** * Returns a stream consisting of the elements of this stream, truncated * to be no longer than {@code maxSize} in length. * *
This is a short-circuiting * stateful intermediate operation. * * @apiNote * While {@code limit()} is generally a cheap operation on sequential * stream pipelines, it can be quite expensive on ordered parallel pipelines, * especially for large values of {@code maxSize}, since {@code limit(n)} * is constrained to return not just any n elements, but the * first n elements in the encounter order. Using an unordered * stream source (such as {@link #generate(DoubleSupplier)}) or removing the * ordering constraint with {@link #unordered()} may result in significant * speedups of {@code limit()} in parallel pipelines, if the semantics of * your situation permit. If consistency with encounter order is required, * and you are experiencing poor performance or memory utilization with * {@code limit()} in parallel pipelines, switching to sequential execution * with {@link #sequential()} may improve performance. * * @param maxSize the number of elements the stream should be limited to * @return the new stream * @throws IllegalArgumentException if {@code maxSize} is negative */ DoubleStream limit(long maxSize); /** * Returns a stream consisting of the remaining elements of this stream * after discarding the first {@code n} elements of the stream. * If this stream contains fewer than {@code n} elements then an * empty stream will be returned. * *
This is a stateful * intermediate operation. * * @apiNote * While {@code skip()} is generally a cheap operation on sequential * stream pipelines, it can be quite expensive on ordered parallel pipelines, * especially for large values of {@code n}, since {@code skip(n)} * is constrained to skip not just any n elements, but the * first n elements in the encounter order. Using an unordered * stream source (such as {@link #generate(DoubleSupplier)}) or removing the * ordering constraint with {@link #unordered()} may result in significant * speedups of {@code skip()} in parallel pipelines, if the semantics of * your situation permit. If consistency with encounter order is required, * and you are experiencing poor performance or memory utilization with * {@code skip()} in parallel pipelines, switching to sequential execution * with {@link #sequential()} may improve performance. * * @param n the number of leading elements to skip * @return the new stream * @throws IllegalArgumentException if {@code n} is negative */ DoubleStream skip(long n); /** * Returns, if this stream is ordered, a stream consisting of the longest * prefix of elements taken from this stream that match the given predicate. * Otherwise returns, if this stream is unordered, a stream consisting of a * subset of elements taken from this stream that match the given predicate. * *
If this stream is ordered then the longest prefix is a contiguous * sequence of elements of this stream that match the given predicate. The * first element of the sequence is the first element of this stream, and * the element immediately following the last element of the sequence does * not match the given predicate. * *
If this stream is unordered, and some (but not all) elements of this * stream match the given predicate, then the behavior of this operation is * nondeterministic; it is free to take any subset of matching elements * (which includes the empty set). * *
Independent of whether this stream is ordered or unordered if all * elements of this stream match the given predicate then this operation * takes all elements (the result is the same as the input), or if no * elements of the stream match the given predicate then no elements are * taken (the result is an empty stream). * *
This is a short-circuiting * stateful intermediate operation. * * @implSpec * The default implementation obtains the {@link #spliterator() spliterator} * of this stream, wraps that spliterator so as to support the semantics * of this operation on traversal, and returns a new stream associated with * the wrapped spliterator. The returned stream preserves the execution * characteristics of this stream (namely parallel or sequential execution * as per {@link #isParallel()}) but the wrapped spliterator may choose to * not support splitting. When the returned stream is closed, the close * handlers for both the returned and this stream are invoked. * * @apiNote * While {@code takeWhile()} is generally a cheap operation on sequential * stream pipelines, it can be quite expensive on ordered parallel * pipelines, since the operation is constrained to return not just any * valid prefix, but the longest prefix of elements in the encounter order. * Using an unordered stream source (such as * {@link #generate(DoubleSupplier)}) or removing the ordering constraint * with {@link #unordered()} may result in significant speedups of * {@code takeWhile()} in parallel pipelines, if the semantics of your * situation permit. If consistency with encounter order is required, and * you are experiencing poor performance or memory utilization with * {@code takeWhile()} in parallel pipelines, switching to sequential * execution with {@link #sequential()} may improve performance. * * @param predicate a non-interfering, * stateless * predicate to apply to elements to determine the longest * prefix of elements. * @return the new stream * @since 9 */ default DoubleStream takeWhile(DoublePredicate predicate) { Objects.requireNonNull(predicate); // Reuses the unordered spliterator, which, when encounter is present, // is safe to use as long as it configured not to split return StreamSupport.doubleStream( new WhileOps.UnorderedWhileSpliterator.OfDouble.Taking(spliterator(), true, predicate), isParallel()).onClose(this::close); } /** * Returns, if this stream is ordered, a stream consisting of the remaining * elements of this stream after dropping the longest prefix of elements * that match the given predicate. Otherwise returns, if this stream is * unordered, a stream consisting of the remaining elements of this stream * after dropping a subset of elements that match the given predicate. * *
If this stream is ordered then the longest prefix is a contiguous * sequence of elements of this stream that match the given predicate. The * first element of the sequence is the first element of this stream, and * the element immediately following the last element of the sequence does * not match the given predicate. * *
If this stream is unordered, and some (but not all) elements of this * stream match the given predicate, then the behavior of this operation is * nondeterministic; it is free to drop any subset of matching elements * (which includes the empty set). * *
Independent of whether this stream is ordered or unordered if all * elements of this stream match the given predicate then this operation * drops all elements (the result is an empty stream), or if no elements of * the stream match the given predicate then no elements are dropped (the * result is the same as the input). * *
This is a stateful * intermediate operation. * * @implSpec * The default implementation obtains the {@link #spliterator() spliterator} * of this stream, wraps that spliterator so as to support the semantics * of this operation on traversal, and returns a new stream associated with * the wrapped spliterator. The returned stream preserves the execution * characteristics of this stream (namely parallel or sequential execution * as per {@link #isParallel()}) but the wrapped spliterator may choose to * not support splitting. When the returned stream is closed, the close * handlers for both the returned and this stream are invoked. * * @apiNote * While {@code dropWhile()} is generally a cheap operation on sequential * stream pipelines, it can be quite expensive on ordered parallel * pipelines, since the operation is constrained to return not just any * valid prefix, but the longest prefix of elements in the encounter order. * Using an unordered stream source (such as * {@link #generate(DoubleSupplier)}) or removing the ordering constraint * with {@link #unordered()} may result in significant speedups of * {@code dropWhile()} in parallel pipelines, if the semantics of your * situation permit. If consistency with encounter order is required, and * you are experiencing poor performance or memory utilization with * {@code dropWhile()} in parallel pipelines, switching to sequential * execution with {@link #sequential()} may improve performance. * * @param predicate a non-interfering, * stateless * predicate to apply to elements to determine the longest * prefix of elements. * @return the new stream * @since 9 */ default DoubleStream dropWhile(DoublePredicate predicate) { Objects.requireNonNull(predicate); // Reuses the unordered spliterator, which, when encounter is present, // is safe to use as long as it configured not to split return StreamSupport.doubleStream( new WhileOps.UnorderedWhileSpliterator.OfDouble.Dropping(spliterator(), true, predicate), isParallel()).onClose(this::close); } /** * Performs an action for each element of this stream. * *
This is a terminal * operation. * *
For parallel stream pipelines, this operation does not * guarantee to respect the encounter order of the stream, as doing so * would sacrifice the benefit of parallelism. For any given element, the * action may be performed at whatever time and in whatever thread the * library chooses. If the action accesses shared state, it is * responsible for providing the required synchronization. * * @param action a * non-interfering action to perform on the elements */ void forEach(DoubleConsumer action); /** * Performs an action for each element of this stream, guaranteeing that * each element is processed in encounter order for streams that have a * defined encounter order. * *
This is a terminal * operation. * * @param action a * non-interfering action to perform on the elements * @see #forEach(DoubleConsumer) */ void forEachOrdered(DoubleConsumer action); /** * Returns an array containing the elements of this stream. * *
This is a terminal * operation. * * @return an array containing the elements of this stream */ double[] toArray(); /** * Performs a reduction on the * elements of this stream, using the provided identity value and an * associative * accumulation function, and returns the reduced value. This is equivalent * to: *
{@code
* double result = identity;
* for (double element : this stream)
* result = accumulator.applyAsDouble(result, element)
* return result;
* }
*
* but is not constrained to execute sequentially.
*
* The {@code identity} value must be an identity for the accumulator * function. This means that for all {@code x}, * {@code accumulator.apply(identity, x)} is equal to {@code x}. * The {@code accumulator} function must be an * associative function. * *
This is a terminal * operation. * * @apiNote Sum, min, max, and average are all special cases of reduction. * Summing a stream of numbers can be expressed as: * *
{@code
* double sum = numbers.reduce(0, (a, b) -> a+b);
* }
*
* or more compactly:
*
* {@code
* double sum = numbers.reduce(0, Double::sum);
* }
*
* While this may seem a more roundabout way to perform an aggregation * compared to simply mutating a running total in a loop, reduction * operations parallelize more gracefully, without needing additional * synchronization and with greatly reduced risk of data races. * * @param identity the identity value for the accumulating function * @param op an associative, * non-interfering, * stateless * function for combining two values * @return the result of the reduction * @see #sum() * @see #min() * @see #max() * @see #average() */ double reduce(double identity, DoubleBinaryOperator op); /** * Performs a reduction on the * elements of this stream, using an * associative accumulation * function, and returns an {@code OptionalDouble} describing the reduced * value, if any. This is equivalent to: *
{@code
* boolean foundAny = false;
* double result = null;
* for (double element : this stream) {
* if (!foundAny) {
* foundAny = true;
* result = element;
* }
* else
* result = accumulator.applyAsDouble(result, element);
* }
* return foundAny ? OptionalDouble.of(result) : OptionalDouble.empty();
* }
*
* but is not constrained to execute sequentially.
*
* The {@code accumulator} function must be an * associative function. * *
This is a terminal * operation. * * @param op an associative, * non-interfering, * stateless * function for combining two values * @return the result of the reduction * @see #reduce(double, DoubleBinaryOperator) */ OptionalDouble reduce(DoubleBinaryOperator op); /** * Performs a mutable * reduction operation on the elements of this stream. A mutable * reduction is one in which the reduced value is a mutable result container, * such as an {@code ArrayList}, and elements are incorporated by updating * the state of the result rather than by replacing the result. This * produces a result equivalent to: *
{@code
* R result = supplier.get();
* for (double element : this stream)
* accumulator.accept(result, element);
* return result;
* }
*
* Like {@link #reduce(double, DoubleBinaryOperator)}, {@code collect} * operations can be parallelized without requiring additional * synchronization. * *
This is a terminal
* operation.
*
* @param The value of a floating-point sum is a function both
* of the input values as well as the order of addition
* operations. The order of addition operations of this method is
* intentionally not defined to allow for implementation
* flexibility to improve the speed and accuracy of the computed
* result.
*
* In particular, this method may be implemented using compensated
* summation or other technique to reduce the error bound in the
* numerical sum compared to a simple summation of {@code double}
* values.
*
* Because of the unspecified order of operations and the
* possibility of using differing summation schemes, the output of
* this method may vary on the same input elements.
*
* Various conditions can result in a non-finite sum being
* computed. This can occur even if the all the elements
* being summed are finite. If any element is non-finite,
* the sum will be non-finite:
*
* This is a terminal
* operation.
*
* @apiNote Elements sorted by increasing absolute magnitude tend
* to yield more accurate results.
*
* @return the sum of elements in this stream
*/
double sum();
/**
* Returns an {@code OptionalDouble} describing the minimum element of this
* stream, or an empty OptionalDouble if this stream is empty. The minimum
* element will be {@code Double.NaN} if any stream element was NaN. Unlike
* the numerical comparison operators, this method considers negative zero
* to be strictly smaller than positive zero. This is a special case of a
* reduction and is
* equivalent to:
* This is a terminal
* operation.
*
* @return an {@code OptionalDouble} containing the minimum element of this
* stream, or an empty optional if the stream is empty
*/
OptionalDouble min();
/**
* Returns an {@code OptionalDouble} describing the maximum element of this
* stream, or an empty OptionalDouble if this stream is empty. The maximum
* element will be {@code Double.NaN} if any stream element was NaN. Unlike
* the numerical comparison operators, this method considers negative zero
* to be strictly smaller than positive zero. This is a
* special case of a
* reduction and is
* equivalent to:
* This is a terminal
* operation.
*
* @return an {@code OptionalDouble} containing the maximum element of this
* stream, or an empty optional if the stream is empty
*/
OptionalDouble max();
/**
* Returns the count of elements in this stream. This is a special case of
* a reduction and is
* equivalent to:
* This is a terminal operation.
*
* @apiNote
* An implementation may choose to not execute the stream pipeline (either
* sequentially or in parallel) if it is capable of computing the count
* directly from the stream source. In such cases no source elements will
* be traversed and no intermediate operations will be evaluated.
* Behavioral parameters with side-effects, which are strongly discouraged
* except for harmless cases such as debugging, may be affected. For
* example, consider the following stream:
* The computed average can vary numerically and have the
* special case behavior as computing the sum; see {@link #sum}
* for details.
*
* The average is a special case of a reduction.
*
* This is a terminal
* operation.
*
* @apiNote Elements sorted by increasing absolute magnitude tend
* to yield more accurate results.
*
* @return an {@code OptionalDouble} containing the average element of this
* stream, or an empty optional if the stream is empty
*/
OptionalDouble average();
/**
* Returns a {@code DoubleSummaryStatistics} describing various summary data
* about the elements of this stream. This is a special
* case of a reduction.
*
* This is a terminal
* operation.
*
* @return a {@code DoubleSummaryStatistics} describing various summary data
* about the elements of this stream
*/
DoubleSummaryStatistics summaryStatistics();
/**
* Returns whether any elements of this stream match the provided
* predicate. May not evaluate the predicate on all elements if not
* necessary for determining the result. If the stream is empty then
* {@code false} is returned and the predicate is not evaluated.
*
* This is a short-circuiting
* terminal operation.
*
* @apiNote
* This method evaluates the existential quantification of the
* predicate over the elements of the stream (for some x P(x)).
*
* @param predicate a non-interfering,
* stateless
* predicate to apply to elements of this stream
* @return {@code true} if any elements of the stream match the provided
* predicate, otherwise {@code false}
*/
boolean anyMatch(DoublePredicate predicate);
/**
* Returns whether all elements of this stream match the provided predicate.
* May not evaluate the predicate on all elements if not necessary for
* determining the result. If the stream is empty then {@code true} is
* returned and the predicate is not evaluated.
*
* This is a short-circuiting
* terminal operation.
*
* @apiNote
* This method evaluates the universal quantification of the
* predicate over the elements of the stream (for all x P(x)). If the
* stream is empty, the quantification is said to be vacuously
* satisfied and is always {@code true} (regardless of P(x)).
*
* @param predicate a non-interfering,
* stateless
* predicate to apply to elements of this stream
* @return {@code true} if either all elements of the stream match the
* provided predicate or the stream is empty, otherwise {@code false}
*/
boolean allMatch(DoublePredicate predicate);
/**
* Returns whether no elements of this stream match the provided predicate.
* May not evaluate the predicate on all elements if not necessary for
* determining the result. If the stream is empty then {@code true} is
* returned and the predicate is not evaluated.
*
* This is a short-circuiting
* terminal operation.
*
* @apiNote
* This method evaluates the universal quantification of the
* negated predicate over the elements of the stream (for all x ~P(x)). If
* the stream is empty, the quantification is said to be vacuously satisfied
* and is always {@code true}, regardless of P(x).
*
* @param predicate a non-interfering,
* stateless
* predicate to apply to elements of this stream
* @return {@code true} if either no elements of the stream match the
* provided predicate or the stream is empty, otherwise {@code false}
*/
boolean noneMatch(DoublePredicate predicate);
/**
* Returns an {@link OptionalDouble} describing the first element of this
* stream, or an empty {@code OptionalDouble} if the stream is empty. If
* the stream has no encounter order, then any element may be returned.
*
* This is a short-circuiting
* terminal operation.
*
* @return an {@code OptionalDouble} describing the first element of this
* stream, or an empty {@code OptionalDouble} if the stream is empty
*/
OptionalDouble findFirst();
/**
* Returns an {@link OptionalDouble} describing some element of the stream,
* or an empty {@code OptionalDouble} if the stream is empty.
*
* This is a short-circuiting
* terminal operation.
*
* The behavior of this operation is explicitly nondeterministic; it is
* free to select any element in the stream. This is to allow for maximal
* performance in parallel operations; the cost is that multiple invocations
* on the same source may not return the same result. (If a stable result
* is desired, use {@link #findFirst()} instead.)
*
* @return an {@code OptionalDouble} describing some element of this stream,
* or an empty {@code OptionalDouble} if the stream is empty
* @see #findFirst()
*/
OptionalDouble findAny();
/**
* Returns a {@code Stream} consisting of the elements of this stream,
* boxed to {@code Double}.
*
* This is an intermediate
* operation.
*
* @return a {@code Stream} consistent of the elements of this stream,
* each boxed to a {@code Double}
*/
Stream The first element (position {@code 0}) in the {@code DoubleStream}
* will be the provided {@code seed}. For {@code n > 0}, the element at
* position {@code n}, will be the result of applying the function {@code f}
* to the element at position {@code n - 1}.
*
* The action of applying {@code f} for one element
* happens-before
* the action of applying {@code f} for subsequent elements. For any given
* element the action may be performed in whatever thread the library
* chooses.
*
* @param seed the initial element
* @param f a function to be applied to the previous element to produce
* a new element
* @return a new sequential {@code DoubleStream}
*/
public static DoubleStream iterate(final double seed, final DoubleUnaryOperator f) {
Objects.requireNonNull(f);
Spliterator.OfDouble spliterator = new Spliterators.AbstractDoubleSpliterator(Long.MAX_VALUE,
Spliterator.ORDERED | Spliterator.IMMUTABLE | Spliterator.NONNULL) {
double prev;
boolean started;
@Override
public boolean tryAdvance(DoubleConsumer action) {
Objects.requireNonNull(action);
double t;
if (started)
t = f.applyAsDouble(prev);
else {
t = seed;
started = true;
}
action.accept(prev = t);
return true;
}
};
return StreamSupport.doubleStream(spliterator, false);
}
/**
* Returns a sequential ordered {@code DoubleStream} produced by iterative
* application of the given {@code next} function to an initial element,
* conditioned on satisfying the given {@code hasNext} predicate. The
* stream terminates as soon as the {@code hasNext} predicate returns false.
*
* {@code DoubleStream.iterate} should produce the same sequence of elements as
* produced by the corresponding for-loop:
* The resulting sequence may be empty if the {@code hasNext} predicate
* does not hold on the seed value. Otherwise the first element will be the
* supplied {@code seed} value, the next element (if present) will be the
* result of applying the {@code next} function to the {@code seed} value,
* and so on iteratively until the {@code hasNext} predicate indicates that
* the stream should terminate.
*
* The action of applying the {@code hasNext} predicate to an element
* happens-before
* the action of applying the {@code next} function to that element. The
* action of applying the {@code next} function for one element
* happens-before the action of applying the {@code hasNext}
* predicate for subsequent elements. For any given element an action may
* be performed in whatever thread the library chooses.
*
* @param seed the initial element
* @param hasNext a predicate to apply to elements to determine when the
* stream must terminate.
* @param next a function to be applied to the previous element to produce
* a new element
* @return a new sequential {@code DoubleStream}
* @since 9
*/
public static DoubleStream iterate(double seed, DoublePredicate hasNext, DoubleUnaryOperator next) {
Objects.requireNonNull(next);
Objects.requireNonNull(hasNext);
Spliterator.OfDouble spliterator = new Spliterators.AbstractDoubleSpliterator(Long.MAX_VALUE,
Spliterator.ORDERED | Spliterator.IMMUTABLE | Spliterator.NONNULL) {
double prev;
boolean started, finished;
@Override
public boolean tryAdvance(DoubleConsumer action) {
Objects.requireNonNull(action);
if (finished)
return false;
double t;
if (started)
t = next.applyAsDouble(prev);
else {
t = seed;
started = true;
}
if (!hasNext.test(t)) {
finished = true;
return false;
}
action.accept(prev = t);
return true;
}
@Override
public void forEachRemaining(DoubleConsumer action) {
Objects.requireNonNull(action);
if (finished)
return;
finished = true;
double t = started ? next.applyAsDouble(prev) : seed;
while (hasNext.test(t)) {
action.accept(t);
t = next.applyAsDouble(t);
}
}
};
return StreamSupport.doubleStream(spliterator, false);
}
/**
* Returns an infinite sequential unordered stream where each element is
* generated by the provided {@code DoubleSupplier}. This is suitable for
* generating constant streams, streams of random elements, etc.
*
* @param s the {@code DoubleSupplier} for generated elements
* @return a new infinite sequential unordered {@code DoubleStream}
*/
public static DoubleStream generate(DoubleSupplier s) {
Objects.requireNonNull(s);
return StreamSupport.doubleStream(
new StreamSpliterators.InfiniteSupplyingSpliterator.OfDouble(Long.MAX_VALUE, s), false);
}
/**
* Creates a lazily concatenated stream whose elements are all the
* elements of the first stream followed by all the elements of the
* second stream. The resulting stream is ordered if both
* of the input streams are ordered, and parallel if either of the input
* streams is parallel. When the resulting stream is closed, the close
* handlers for both input streams are invoked.
*
* This method operates on the two input streams and binds each stream
* to its source. As a result subsequent modifications to an input stream
* source may not be reflected in the concatenated stream result.
*
* @implNote
* Use caution when constructing streams from repeated concatenation.
* Accessing an element of a deeply concatenated stream can result in deep
* call chains, or even {@code StackOverflowError}.
*
* @apiNote
* To preserve optimization opportunities this method binds each stream to
* its source and accepts only two streams as parameters. For example, the
* exact size of the concatenated stream source can be computed if the exact
* size of each input stream source is known.
* To concatenate more streams without binding, or without nested calls to
* this method, try creating a stream of streams and flat-mapping with the
* identity function, for example:
* A stream builder has a lifecycle, which starts in a building
* phase, during which elements can be added, and then transitions to a built
* phase, after which elements may not be added. The built phase
* begins when the {@link #build()} method is called, which creates an
* ordered stream whose elements are the elements that were added to the
* stream builder, in the order they were added.
*
* @see DoubleStream#builder()
* @since 1.8
*/
public interface Builder extends DoubleConsumer {
/**
* Adds an element to the stream being built.
*
* @throws IllegalStateException if the builder has already transitioned
* to the built state
*/
@Override
void accept(double t);
/**
* Adds an element to the stream being built.
*
* @implSpec
* The default implementation behaves as if:
* This is a functional interface
* whose functional method is {@link #accept(double, DoubleConsumer)}.
*
* @see DoubleStream#mapMulti(DoubleMapMultiConsumer)
*
* @since 16
*/
@FunctionalInterface
interface DoubleMapMultiConsumer {
/**
* Replaces the given {@code value} with zero or more values by feeding the mapped
* values to the {@code dc} consumer.
*
* @param value the double value coming from upstream
* @param dc a {@code DoubleConsumer} accepting the mapped values
*/
void accept(double value, DoubleConsumer dc);
}
}
{@code
* return reduce(0, Double::sum);
* }
*
* However, since floating-point summation is not exact, the above
* code is not necessarily equivalent to the summation computation
* done by this method.
*
*
*
*
*
* It is possible for intermediate sums of finite values to
* overflow into opposite-signed infinities; if that occurs, the
* final sum will be NaN even if the elements are all
* finite.
*
* If all the elements are zero, the sign of zero is
* not guaranteed to be preserved in the final sum.
*
*
*
*
*
* {@code
* return reduce(Double::min);
* }
*
* {@code
* return reduce(Double::max);
* }
*
* {@code
* return mapToLong(e -> 1L).sum();
* }
*
* {@code
* DoubleStream s = DoubleStream.of(1, 2, 3, 4);
* long count = s.peek(System.out::println).count();
* }
* The number of elements covered by the stream source is known and the
* intermediate operation, {@code peek}, does not inject into or remove
* elements from the stream (as may be the case for {@code flatMap} or
* {@code filter} operations). Thus the count is 4 and there is no need to
* execute the pipeline and, as a side-effect, print out the elements.
*
* @return the count of elements in this stream
*/
long count();
/**
* Returns an {@code OptionalDouble} describing the arithmetic
* mean of elements of this stream, or an empty optional if this
* stream is empty.
*
* {@code
* for (double index=seed; hasNext.test(index); index = next.applyAsDouble(index)) {
* ...
* }
* }
*
* {@code
* DoubleStream concat = Stream.of(s1, s2, s3, s4).flatMapToDouble(s -> s);
* }
*
* @param a the first stream
* @param b the second stream
* @return the concatenation of the two input streams
*/
public static DoubleStream concat(DoubleStream a, DoubleStream b) {
Objects.requireNonNull(a);
Objects.requireNonNull(b);
Spliterator.OfDouble split = new Streams.ConcatSpliterator.OfDouble(
a.spliterator(), b.spliterator());
DoubleStream stream = StreamSupport.doubleStream(split, a.isParallel() || b.isParallel());
return stream.onClose(Streams.composedClose(a, b));
}
/**
* A mutable builder for a {@code DoubleStream}.
*
* {@code
* accept(t)
* return this;
* }
*
* @param t the element to add
* @return {@code this} builder
* @throws IllegalStateException if the builder has already transitioned
* to the built state
*/
default Builder add(double t) {
accept(t);
return this;
}
/**
* Builds the stream, transitioning this builder to the built state.
* An {@code IllegalStateException} is thrown if there are further
* attempts to operate on the builder after it has entered the built
* state.
*
* @return the built stream
* @throws IllegalStateException if the builder has already transitioned
* to the built state
*/
DoubleStream build();
}
/**
* Represents an operation that accepts a {@code double}-valued argument
* and a DoubleConsumer, and returns no result. This functional interface is
* used by {@link DoubleStream#mapMulti(DoubleMapMultiConsumer) DoubleStream.mapMulti}
* to replace a double value with zero or more double values.
*
*