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 //////////////////////////////////////////////////////////////////////////////
 //
 // (C) Copyright Ion Gaztanaga 2015-2016.
 // Distributed under the Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt or copy at
 // http://www.boost.org/LICENSE_1_0.txt)
 //
 // See http://www.boost.org/libs/move for documentation.
 //
 //////////////////////////////////////////////////////////////////////////////
 
 #ifndef BOOST_MOVE_ADAPTIVE_MERGE_HPP
 #define BOOST_MOVE_ADAPTIVE_MERGE_HPP
 
 #include <boost/move/detail/config_begin.hpp>
 #include <boost/move/algo/detail/adaptive_sort_merge.hpp>
 #include <cassert>
 
 #if defined(BOOST_CLANG) || (defined(BOOST_GCC) && (BOOST_GCC >= 40600))
 #pragma GCC diagnostic push
 #pragma GCC diagnostic ignored "-Wsign-conversion"
 #pragma GCC diagnostic ignored "-Wconversion"
 #endif
 
 namespace boost {
 namespace movelib {
 
 ///@cond
 namespace detail_adaptive {
 
 template<class RandIt, class Compare, class XBuf>
 inline void adaptive_merge_combine_blocks( RandIt first
                                       , typename iter_size<RandIt>::type len1
                                       , typename iter_size<RandIt>::type len2
                                       , typename iter_size<RandIt>::type collected
                                       , typename iter_size<RandIt>::type n_keys
                                       , typename iter_size<RandIt>::type l_block
                                       , bool use_internal_buf
                                       , bool xbuf_used
                                       , Compare comp
                                       , XBuf & xbuf
                                       )
 {
    typedef typename iter_size<RandIt>::type       size_type;
 
    size_type const len = size_type(len1+len2);
    size_type const l_combine  = size_type(len-collected);
    size_type const l_combine1 = size_type(len1-collected);
 
     if(n_keys){
       RandIt const first_data = first+collected;
       RandIt const keys = first;
       BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2("   A combine: ", len);
       if(xbuf_used){
          if(xbuf.size() < l_block){
             xbuf.initialize_until(l_block, *first);
          }
          assert(xbuf.size() >= l_block);
          size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
          combine_params( keys, comp, l_combine
                            , l_combine1, l_block, xbuf
                            , n_block_a, n_block_b, l_irreg1, l_irreg2);   //Outputs
          op_merge_blocks_with_buf
             (keys, comp, first_data, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp, move_op(), xbuf.data());
          BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1("   A mrg xbf: ", len);
       }
       else{
          size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
          combine_params( keys, comp, l_combine
                            , l_combine1, l_block, xbuf
                            , n_block_a, n_block_b, l_irreg1, l_irreg2);   //Outputs
          if(use_internal_buf){
             op_merge_blocks_with_buf
                ( keys, comp, first_data, l_block, l_irreg1, n_block_a, n_block_b
                , l_irreg2, comp, swap_op(), first_data-l_block);
             BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2("   A mrg buf: ", len);
          }
          else{
             merge_blocks_bufferless
                (keys, comp, first_data, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp);
             BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1("   A mrg nbf: ", len);
          }
       }
    }
    else{
       xbuf.shrink_to_fit(l_block);
       if(xbuf.size() < l_block){
          xbuf.initialize_until(l_block, *first);
       }
       size_type *const uint_keys = xbuf.template aligned_trailing<size_type>(l_block);
       size_type n_block_a, n_block_b, l_irreg1, l_irreg2;
       combine_params( uint_keys, less(), l_combine
                      , l_combine1, l_block, xbuf
                      , n_block_a, n_block_b, l_irreg1, l_irreg2, true);   //Outputs
       BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2("   A combine: ", len);
       assert(xbuf.size() >= l_block);
       op_merge_blocks_with_buf
          (uint_keys, less(), first, l_block, l_irreg1, n_block_a, n_block_b, l_irreg2, comp, move_op(), xbuf.data());
       xbuf.clear();
       BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1("   A mrg buf: ", len);
    }
 }
 
 template<class RandIt, class Compare, class XBuf>
 inline void adaptive_merge_final_merge( RandIt first
                                       , typename iter_size<RandIt>::type len1
                                       , typename iter_size<RandIt>::type len2
                                       , typename iter_size<RandIt>::type collected
                                       , typename iter_size<RandIt>::type l_intbuf
                                       , typename iter_size<RandIt>::type //l_block
                                       , bool //use_internal_buf
                                       , bool xbuf_used
                                       , Compare comp
                                       , XBuf & xbuf
                                       )
 {
    typedef typename iter_size<RandIt>::type       size_type;
 
    size_type n_keys = size_type(collected-l_intbuf);
    size_type len = size_type(len1+len2);
    if (!xbuf_used || n_keys) {
       xbuf.clear();
       const size_type middle = xbuf_used && n_keys ? n_keys: collected;
       unstable_sort(first, first + middle, comp, xbuf);
       BOOST_MOVE_ADAPTIVE_SORT_PRINT_L2("   A k/b srt: ", len);
       stable_merge(first, first + middle, first + len, comp, xbuf);
    }
    BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1("   A fin mrg: ", len);
 }
 
 template<class SizeType>
 inline static SizeType adaptive_merge_n_keys_without_external_keys(SizeType l_block, SizeType len1, SizeType len2, SizeType l_intbuf)
 {
    typedef SizeType size_type;
    //This is the minimum number of keys to implement the ideal algorithm
    size_type n_keys = size_type(len1/l_block + len2/l_block);
    const size_type second_half_blocks = size_type(len2/l_block);
    const size_type first_half_aux = size_type(len1 - l_intbuf);
    while(n_keys >= ((first_half_aux-n_keys)/l_block + second_half_blocks)){
       --n_keys;
    }
    ++n_keys;
    return n_keys;
 }
 
 template<class SizeType>
 inline static SizeType adaptive_merge_n_keys_with_external_keys(SizeType l_block, SizeType len1, SizeType len2, SizeType l_intbuf)
 {
    typedef SizeType size_type;
    //This is the minimum number of keys to implement the ideal algorithm
    size_type n_keys = size_type((len1-l_intbuf)/l_block + len2/l_block);
    return n_keys;
 }
 
 template<class SizeType, class Xbuf>
 inline SizeType adaptive_merge_n_keys_intbuf(SizeType &rl_block, SizeType len1, SizeType len2, Xbuf & xbuf, SizeType &l_intbuf_inout)
 {
    typedef SizeType size_type;
    size_type l_block = rl_block;
    size_type l_intbuf = xbuf.capacity() >= l_block ? 0u : l_block;
 
    if (xbuf.capacity() > l_block){
       l_block = xbuf.capacity();
    }
 
    //This is the minimum number of keys to implement the ideal algorithm
    size_type n_keys = adaptive_merge_n_keys_without_external_keys(l_block, len1, len2, l_intbuf);
    assert(n_keys >= ((len1-l_intbuf-n_keys)/l_block + len2/l_block));
 
    if(xbuf.template supports_aligned_trailing<size_type>
       ( l_block
       , adaptive_merge_n_keys_with_external_keys(l_block, len1, len2, l_intbuf)))
    {
       n_keys = 0u;
    }
    l_intbuf_inout = l_intbuf;
    rl_block = l_block;
    return n_keys;
 }
 
 // Main explanation of the merge algorithm.
 //
 // csqrtlen = ceil(sqrt(len));
 //
 // * First, csqrtlen [to be used as buffer] + (len/csqrtlen - 1) [to be used as keys] => to_collect
 //   unique elements are extracted from elements to be sorted and placed in the beginning of the range.
 //
 // * Step "combine_blocks": the leading (len1-to_collect) elements plus trailing len2 elements
 //   are merged with a non-trivial ("smart") algorithm to form an ordered range trailing "len-to_collect" elements.
 //
 //   Explanation of the "combine_blocks" step:
 //
 //         * Trailing [first+to_collect, first+len1) elements are divided in groups of cqrtlen elements.
 //           Remaining elements that can't form a group are grouped in front of those elements.
 //         * Trailing [first+len1, first+len1+len2) elements are divided in groups of cqrtlen elements.
 //           Remaining elements that can't form a group are grouped in the back of those elements.
 //         * In parallel the following two steps are performed:
 //             *  Groups are selection-sorted by first or last element (depending whether they are going
 //                to be merged to left or right) and keys are reordered accordingly as an imitation-buffer.
 //             * Elements of each block pair are merged using the csqrtlen buffer taking into account
 //                if they belong to the first half or second half (marked by the key).
 //
 // * In the final merge step leading "to_collect" elements are merged with rotations
 //   with the rest of merged elements in the "combine_blocks" step.
 //
 // Corner cases:
 //
 // * If no "to_collect" elements can be extracted:
 //
 //    * If more than a minimum number of elements is extracted
 //      then reduces the number of elements used as buffer and keys in the
 //      and "combine_blocks" steps. If "combine_blocks" has no enough keys due to this reduction
 //      then uses a rotation based smart merge.
 //
 //    * If the minimum number of keys can't be extracted, a rotation-based merge is performed.
 //
 // * If auxiliary memory is more or equal than min(len1, len2), a buffered merge is performed.
 //
 // * If the len1 or len2 are less than 2*csqrtlen then a rotation-based merge is performed.
 //
 // * If auxiliary memory is more than csqrtlen+n_keys*sizeof(std::size_t),
 //   then no csqrtlen need to be extracted and "combine_blocks" will use integral
 //   keys to combine blocks.
 template<class RandIt, class Compare, class XBuf>
 void adaptive_merge_impl
    ( RandIt first
    , typename iter_size<RandIt>::type len1
    , typename iter_size<RandIt>::type len2
    , Compare comp
    , XBuf & xbuf
    )
 {
    typedef typename iter_size<RandIt>::type size_type;
 
    if(xbuf.capacity() >= min_value<size_type>(len1, len2)){
       buffered_merge( first, first+len1
                     , first + len1+len2, comp, xbuf);
    }
    else{
       const size_type len = size_type(len1+len2);
       //Calculate ideal parameters and try to collect needed unique keys
       size_type l_block = size_type(ceil_sqrt(len));
 
       //One range is not big enough to extract keys and the internal buffer so a
       //rotation-based based merge will do just fine
       if(len1 <= l_block*2 || len2 <= l_block*2){
          merge_bufferless(first, first+len1, first+len1+len2, comp);
          return;
       }
 
       //Detail the number of keys and internal buffer. If xbuf has enough memory, no
       //internal buffer is needed so l_intbuf will remain 0.
       size_type l_intbuf = 0;
       size_type n_keys = adaptive_merge_n_keys_intbuf(l_block, len1, len2, xbuf, l_intbuf);
       size_type const to_collect = size_type(l_intbuf+n_keys);
       //Try to extract needed unique values from the first range
       size_type const collected  = collect_unique(first, first+len1, to_collect, comp, xbuf);
       BOOST_MOVE_ADAPTIVE_SORT_PRINT_L1("\n   A collect: ", len);
 
       //Not the minimum number of keys is not available on the first range, so fallback to rotations
       if(collected != to_collect && collected < 4){
          merge_bufferless(first, first+collected, first+len1, comp);
          merge_bufferless(first, first + len1, first + len1 + len2, comp);
          return;
       }
 
       //If not enough keys but more than minimum, adjust the internal buffer and key count
       bool use_internal_buf = collected == to_collect;
       if (!use_internal_buf){
          l_intbuf = 0u;
          n_keys = collected;
          l_block  = lblock_for_combine(l_intbuf, n_keys, len, use_internal_buf);
          //If use_internal_buf is false, then then internal buffer will be zero and rotation-based combination will be used
          l_intbuf = use_internal_buf ? l_block : 0u;
       }
 
       bool const xbuf_used = collected == to_collect && xbuf.capacity() >= l_block;
       //Merge trailing elements using smart merges
       adaptive_merge_combine_blocks(first, len1, len2, collected,   n_keys, l_block, use_internal_buf, xbuf_used, comp, xbuf);
       //Merge buffer and keys with the rest of the values
       adaptive_merge_final_merge   (first, len1, len2, collected, l_intbuf, l_block, use_internal_buf, xbuf_used, comp, xbuf);
    }
 }
 
 }  //namespace detail_adaptive {
 
 ///@endcond
 
 //! <b>Effects</b>: Merges two consecutive sorted ranges [first, middle) and [middle, last)
 //!   into one sorted range [first, last) according to the given comparison function comp.
 //!   The algorithm is stable (if there are equivalent elements in the original two ranges,
 //!   the elements from the first range (preserving their original order) precede the elements
 //!   from the second range (preserving their original order).
 //!
 //! <b>Requires</b>:
 //!   - RandIt must meet the requirements of ValueSwappable and RandomAccessIterator.
 //!   - The type of dereferenced RandIt must meet the requirements of MoveAssignable and MoveConstructible.
 //!
 //! <b>Parameters</b>:
 //!   - first: the beginning of the first sorted range. 
 //!   - middle: the end of the first sorted range and the beginning of the second
 //!   - last: the end of the second sorted range
 //!   - comp: comparison function object which returns true if the first argument is is ordered before the second.
 //!   - uninitialized, uninitialized_len: raw storage starting on "uninitialized", able to hold "uninitialized_len"
 //!      elements of type iterator_traits<RandIt>::value_type. Maximum performance is achieved when uninitialized_len
 //!      is min(std::distance(first, middle), std::distance(middle, last)).
 //!
 //! <b>Throws</b>: If comp throws or the move constructor, move assignment or swap of the type
 //!   of dereferenced RandIt throws.
 //!
 //! <b>Complexity</b>: Always K x O(N) comparisons and move assignments/constructors/swaps.
 //!   Constant factor for comparisons and data movement is minimized when uninitialized_len
 //!   is min(std::distance(first, middle), std::distance(middle, last)).
 //!   Pretty good enough performance is achieved when uninitialized_len is
 //!   ceil(sqrt(std::distance(first, last)))*2.
 //!
 //! <b>Caution</b>: Experimental implementation, not production-ready.
 template<class RandIt, class Compare>
 void adaptive_merge( RandIt first, RandIt middle, RandIt last, Compare comp
                 , typename iterator_traits<RandIt>::value_type* uninitialized = 0
                 , typename iter_size<RandIt>::type uninitialized_len = 0)
 {
    typedef typename iter_size<RandIt>::type  size_type;
    typedef typename iterator_traits<RandIt>::value_type value_type;
 
    if (first == middle || middle == last){
       return;
    }
 
    //Reduce ranges to merge if possible
    do {
       if (comp(*middle, *first)){
          break;
       }
       ++first;
       if (first == middle)
          return;
    } while(1);
 
    RandIt first_high(middle);
    --first_high;
    do {
       --last;
       if (comp(*last, *first_high)){
          ++last;
          break;
       }
       if (last == middle)
          return;
    } while(1);
 
    ::boost::movelib::adaptive_xbuf<value_type, value_type*, size_type> xbuf(uninitialized, size_type(uninitialized_len));
    ::boost::movelib::detail_adaptive::adaptive_merge_impl(first, size_type(middle - first), size_type(last - middle), comp, xbuf);
 }
 
 }  //namespace movelib {
 }  //namespace boost {
 
 #if defined(BOOST_CLANG) || (defined(BOOST_GCC) && (BOOST_GCC >= 40600))
 #pragma GCC diagnostic pop
 #endif
 
 #include <boost/move/detail/config_end.hpp>
 
 #endif   //#define BOOST_MOVE_ADAPTIVE_MERGE_HPP

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