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##### partial_sort

###### Prototype

    template<class RandomAccessRange>
    RandomAccessRange& partial_sort(
        RandomAccessRange& rng,
        typename range_iterator<RandomAccessRange>::type middle);

    template<class RandomAccessRange>
    const RandomAccessRange& partial_sort(
        const RandomAccessRange& rng,
        typename range_iterator<const RandomAccessRange>::type middle);

    template<class RandomAccessRange>
    RandomAccessRange& partial_sort(
        RandomAccessRange& rng,
        typename range_iterator<RandomAccessRange>::type middle,
        BinaryPredicate sort_pred);

    template<class RandomAccessRange>
    const RandomAccessRange& partial_sort(
        const RandomAccessRange& rng,
        typename range_iterator<const RandomAccessRange>::type middle,
        BinaryPredicate sort_pred);

###### Description

`partial_sort` rearranges the elements in `rng`. It places the smallest `distance(begin(rng), middle)` elements, sorted in ascending order, into the range `[begin(rng), middle)`. The remaining elements are placed in an unspecified order into `[middle, last)`.

The non-predicative versions of this function specify that one element is less than another by using `operator<()`. The predicate versions use the predicate instead.

###### Definition

Defined in the header file `boost/range/algorithm/partial_sort.hpp`

###### Requirements

For the non-predicate version:

- `RandomAccessRange` is a model of the Random Access Range Concept.
- `RandomAccessRange` is mutable.
- `RandomAccessRange`'s value type is a model of the `LessThanComparableConcept`.
- The ordering relation on `RandomAccessRange`'s value type is a strict weak ordering, as defined in the `LessThanComparableConcept` requirements.

For the predicate version:

- `RandomAccessRange` is a model of the Random Access Range Concept.
- `RandomAccessRange` is mutable.
- `BinaryPredicate` is a model of the `StrictWeakOrderingConcept`.
- `RandomAccessRange`'s value type is convertible to both of `BinaryPredicate`'s argument types.

###### Complexity

Approximately `distance(rng) * log(distance(begin(rng), middle))` comparisons.