Interface DoubleStream

Methods

filter

DoubleStream filter(DoublePredicate predicate)

Parameters:

predicate - a non-interfering, stateless predicate to apply to each element to determine if it should be included

Returns:

the new stream

map

DoubleStream map(DoubleUnaryOperator mapper)

Parameters:

mapper - a non-interfering, stateless function to apply to each element

Returns:

the new stream

mapToObj

<U> Stream<U> mapToObj(DoubleFunction<? extends U> mapper)

Type Parameters:

U - the element type of the new stream

Parameters:

mapper - a non-interfering, stateless function to apply to each element

Returns:

the new stream

mapToInt

IntStream mapToInt(DoubleToIntFunction mapper)

Parameters:

mapper - a non-interfering, stateless function to apply to each element

Returns:

the new stream

mapToLong

LongStream mapToLong(DoubleToLongFunction mapper)

Parameters:

mapper - a non-interfering, stateless function to apply to each element

Returns:

the new stream

flatMap

DoubleStream flatMap(DoubleFunction<? extends DoubleStream> mapper)

Parameters:

mapper - a non-interfering, stateless function to apply to each element which produces a DoubleStream of new values

Returns:

the new stream

See Also:

Stream.flatMap(Function)

distinct

DoubleStream distinct()

Returns:

the result stream

sorted

DoubleStream sorted()

Returns:

the result stream

peek

DoubleStream peek(DoubleConsumer action)

API Note:

This method exists mainly to support debugging, where you want to see the elements as they flow past a certain point in a pipeline:

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 findFirst, or in the example described in count()), the action will not be invoked for those elements.

Parameters:

action - a non-interfering action to perform on the elements as they are consumed from the stream

Returns:

the new stream

limit

DoubleStream limit(long maxSize)

API Note:

While limit() is generally a cheap operation on sequential stream pipelines, it can be quite expensive on ordered parallel pipelines, especially for large values of maxSize, since 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 generate(DoubleSupplier)) or removing the ordering constraint with BaseStream.unordered() may result in significant speedups of 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 limit() in parallel pipelines, switching to sequential execution with BaseStream.sequential() may improve performance.

Parameters:

maxSize - the number of elements the stream should be limited to

Returns:

the new stream

Throws:

IllegalArgumentException - if maxSize is negative

skip

DoubleStream skip(long n)

API Note:

While skip() is generally a cheap operation on sequential stream pipelines, it can be quite expensive on ordered parallel pipelines, especially for large values of n, since 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 generate(DoubleSupplier)) or removing the ordering constraint with BaseStream.unordered() may result in significant speedups of 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 skip() in parallel pipelines, switching to sequential execution with BaseStream.sequential() may improve performance.

Parameters:

n - the number of leading elements to skip

Returns:

the new stream

Throws:

IllegalArgumentException - if n is negative

takeWhile

default DoubleStream takeWhile(DoublePredicate predicate)

API Note:

While 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 generate(DoubleSupplier)) or removing the ordering constraint with BaseStream.unordered() may result in significant speedups of 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 takeWhile() in parallel pipelines, switching to sequential execution with BaseStream.sequential() may improve performance.

Implementation Requirements:

The default implementation obtains the 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 BaseStream.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.

Parameters:

predicate - a non-interfering, stateless predicate to apply to elements to determine the longest prefix of elements.

Returns:

the new stream

Since:

9

dropWhile

default DoubleStream dropWhile(DoublePredicate predicate)

API Note:

While 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 generate(DoubleSupplier)) or removing the ordering constraint with BaseStream.unordered() may result in significant speedups of 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 dropWhile() in parallel pipelines, switching to sequential execution with BaseStream.sequential() may improve performance.

Implementation Requirements:

The default implementation obtains the 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 BaseStream.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.

Parameters:

predicate - a non-interfering, stateless predicate to apply to elements to determine the longest prefix of elements.

Returns:

the new stream

Since:

9

forEach

void forEach(DoubleConsumer action)

Parameters:

action - a non-interfering action to perform on the elements

forEachOrdered

void forEachOrdered(DoubleConsumer action)

Parameters:

action - a non-interfering action to perform on the elements

See Also:

forEach(DoubleConsumer)

toArray

double[] toArray()

Returns:

an array containing the elements of this stream

reduce

double reduce(double identity,
              DoubleBinaryOperator op)

double result = identity;
     for (double element : this stream)
         result = accumulator.applyAsDouble(result, element)
     return result;

API Note:

Sum, min, max, and average are all special cases of reduction. Summing a stream of numbers can be expressed as:

double sum = numbers.reduce(0, (a, b) -> a+b);

or more compactly:

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.

Parameters:

identity - the identity value for the accumulating function

op - an associative, non-interfering, stateless function for combining two values

Returns:

the result of the reduction

See Also:

sum(), min(), max(), average()

reduce

OptionalDouble reduce(DoubleBinaryOperator op)

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();

Parameters:

op - an associative, non-interfering, stateless function for combining two values

Returns:

the result of the reduction

See Also:

reduce(double, DoubleBinaryOperator)

collect

<R> R collect(Supplier<R> supplier,
              ObjDoubleConsumer<R> accumulator,
              BiConsumer<R,​R> combiner)

R result = supplier.get();
     for (double element : this stream)
         accumulator.accept(result, element);
     return result;

Type Parameters:

R - the type of the mutable result container

Parameters:

supplier - a function that creates a new mutable result container. For a parallel execution, this function may be called multiple times and must return a fresh value each time.

accumulator - an associative, non-interfering, stateless function that must fold an element into a result container.

combiner - an associative, non-interfering, stateless function that accepts two partial result containers and merges them, which must be compatible with the accumulator function. The combiner function must fold the elements from the second result container into the first result container.

Returns:

the result of the reduction

See Also:

Stream.collect(Supplier, BiConsumer, BiConsumer)

sum

double sum()

return reduce(0, Double::sum);

API Note:

Elements sorted by increasing absolute magnitude tend to yield more accurate results.

Returns:

the sum of elements in this stream

min

OptionalDouble min()

return reduce(Double::min);

Returns:

an OptionalDouble containing the minimum element of this stream, or an empty optional if the stream is empty

max

OptionalDouble max()

return reduce(Double::max);

Returns:

an OptionalDouble containing the maximum element of this stream, or an empty optional if the stream is empty

count

long count()

return mapToLong(e -> 1L).sum();

API Note:

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:

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, peek, does not inject into or remove elements from the stream (as may be the case for flatMap or 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.

Returns:

the count of elements in this stream

average

OptionalDouble average()

API Note:

Elements sorted by increasing absolute magnitude tend to yield more accurate results.

Returns:

an OptionalDouble containing the average element of this stream, or an empty optional if the stream is empty

summaryStatistics

DoubleSummaryStatistics summaryStatistics()

Returns:

a DoubleSummaryStatistics describing various summary data about the elements of this stream

anyMatch

boolean anyMatch(DoublePredicate predicate)

API Note:

This method evaluates the existential quantification of the predicate over the elements of the stream (for some x P(x)).

Parameters:

predicate - a non-interfering, stateless predicate to apply to elements of this stream

Returns:

true if any elements of the stream match the provided predicate, otherwise false

allMatch

boolean allMatch(DoublePredicate predicate)

API Note:

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 true (regardless of P(x)).

Parameters:

predicate - a non-interfering, stateless predicate to apply to elements of this stream

Returns:

true if either all elements of the stream match the provided predicate or the stream is empty, otherwise false

noneMatch

boolean noneMatch(DoublePredicate predicate)

API Note:

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 true, regardless of P(x).

Parameters:

predicate - a non-interfering, stateless predicate to apply to elements of this stream

Returns:

true if either no elements of the stream match the provided predicate or the stream is empty, otherwise false

findFirst

OptionalDouble findFirst()

Returns:

an OptionalDouble describing the first element of this stream, or an empty OptionalDouble if the stream is empty

findAny

OptionalDouble findAny()

Returns:

an OptionalDouble describing some element of this stream, or an empty OptionalDouble if the stream is empty

See Also:

findFirst()

boxed

Stream<Double> boxed()

Returns:

a Stream consistent of the elements of this stream, each boxed to a Double

builder

static DoubleStream.Builder builder()

Returns a builder for a DoubleStream.

Returns:

a stream builder

empty

static DoubleStream empty()

Returns an empty sequential DoubleStream.

Returns:

an empty sequential stream

of

static DoubleStream of(double t)

Returns a sequential DoubleStream containing a single element.

Parameters:

t - the single element

Returns:

a singleton sequential stream

of

static DoubleStream of(double... values)

Returns a sequential ordered stream whose elements are the specified values.

Parameters:

values - the elements of the new stream

Returns:

the new stream

iterate

static DoubleStream iterate(double seed,
                            DoubleUnaryOperator f)

Parameters:

seed - the initial element

f - a function to be applied to the previous element to produce a new element

Returns:

a new sequential DoubleStream

iterate

static DoubleStream iterate(double seed,
                            DoublePredicate hasNext,
                            DoubleUnaryOperator next)

for (double index=seed; hasNext.test(index); index = next.applyAsDouble(index)) {
         ...
     }

Parameters:

seed - the initial element

hasNext - a predicate to apply to elements to determine when the stream must terminate.

next - a function to be applied to the previous element to produce a new element

Returns:

a new sequential DoubleStream

Since:

9

generate

static DoubleStream generate(DoubleSupplier s)

Returns an infinite sequential unordered stream where each element is generated by the provided DoubleSupplier. This is suitable for generating constant streams, streams of random elements, etc.

Parameters:

s - the DoubleSupplier for generated elements

Returns:

a new infinite sequential unordered DoubleStream

concat

static DoubleStream concat(DoubleStream a,
                           DoubleStream b)

API Note:

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:

DoubleStream concat = Stream.of(s1, s2, s3, s4).flatMapToDouble(s -> s);

Implementation Note:

Use caution when constructing streams from repeated concatenation. Accessing an element of a deeply concatenated stream can result in deep call chains, or even StackOverflowError.

Parameters:

a - the first stream

b - the second stream

Returns:

the concatenation of the two input streams