// ==========================================================================
// SeqAn - The Library for Sequence Analysis
// ==========================================================================
// Copyright (c) 2006-2018, Knut Reinert, FU Berlin
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
// * Neither the name of Knut Reinert or the FU Berlin nor the names of
// its contributors may be used to endorse or promote products derived
// from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL KNUT REINERT OR THE FU BERLIN BE LIABLE
// FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
// DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
// SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
// CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
// LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
// OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
// DAMAGE.
//
// ==========================================================================
// Author: Stephan Aiche <stephan.aiche@fu-berlin.de>
// ==========================================================================
#ifndef SEQAN_INCLUDE_SEQAN_ALIGN_GLOBAL_ALIGNMENT_MYERS_HIRSCHBERG_IMPL_H_
#define SEQAN_INCLUDE_SEQAN_ALIGN_GLOBAL_ALIGNMENT_MYERS_HIRSCHBERG_IMPL_H_
#include <bitset>
namespace seqan {
// ============================================================================
// Forwards
// ============================================================================
// ============================================================================
// Tags, Classes, Enums
// ============================================================================
// ============================================================================
// Metafunctions
// ============================================================================
// ============================================================================
// Functions
// ============================================================================
// ----------------------------------------------------------------------------
// Function _writeDebugMatrix()
// ----------------------------------------------------------------------------
#ifdef MYERS_HIRSCHBERG_VERBOSE
template<typename TSource>
void _writeDebugMatrix(TSource s1,TSource s2)
{
//IOREV _notio_ not relevant for iorev
int l1 = length(s1);
int l2 = length(s2);
int i,j,sg,sd;
String<String<int> > fMatrix,rMatrix,tMatrix;
resize(fMatrix,l1 + 1);
resize(rMatrix,l1 + 1);
resize(tMatrix,l1 + 1);
for(i = 0;i <= l1;++i)
{
resize(fMatrix[i],l2 + 1);
resize(rMatrix[i],l2 + 1);
resize(tMatrix[i],l2 + 1);
}
for(i = 0;i <= l1;++i)
fMatrix[i][0] = i * (-1);
for(i = l1;i >= 0;--i)
rMatrix[i][l2] = (l1 - i) * (-1);
// calculate forward matrix
for(j = 1;j <= l2;++j)
{
fMatrix[0][j] = j*(-1);
for(i = 1;i <= l1;++i)
{
sg = -1 + ((fMatrix[i-1][j] > fMatrix[i][j-1]) ? fMatrix[i-1][j] : fMatrix[i][j-1]);
sd = fMatrix[i-1][j-1] + ((s1[i - 1] == s2[j-1]) ? 0 : -1 );
fMatrix[i][j] = ((sg > sd) ? sg : sd);
}
}
// calculate reverse matrix
for(j = l2 - 1;j >= 0;--j)
{
rMatrix[l1][j] = (l2 - j)*(-1);
for(i = l1 - 1;i >= 0;--i)
{
sg = -1 + ((rMatrix[i+1][j] > rMatrix[i][j+1]) ? rMatrix[i+1][j] : rMatrix[i][j+1]);
sd = rMatrix[i+1][j+1] + ((s1[i] == s2[j]) ? 0 : -1 );
rMatrix[i][j] = ((sg > sd) ? sg : sd);
}
}
// print fMatrix
std::cout << ";-;";
for(i = 0;i < l1;++i)
std::cout << s1[i] << ";";
std::cout << std::endl << "-;";
for(j = 0;j <= l2;++j)
{
if(j != 0) std::cout << s2[j-1] << ";";
for(i = 0;i <= l1;++i)
{
std::cout << fMatrix[i][j] << ";";
}
std::cout << std::endl;
}
// print rMatrix
std::cout << ";";
for(i = 0;i < l1;++i)
std::cout << s1[i] << ";";
std::cout << "-;" << std::endl;
for(j = 0;j <= l2;++j)
{
if(j != l2) std::cout << s2[j] << ";";
else std::cout << "-;";
for(i = 0;i <= l1;++i)
{
std::cout << rMatrix[i][j] << ";";
}
std::cout << std::endl;
}
// fill and print target matrix
std::cout << ";-;";
for(i = 0;i < l1;++i)
std::cout << s1[i] << ";";
std::cout << std::endl << "-;";
for(j = 0;j <= l2;++j)
{
if(j != 0) std::cout << s2[j-1] << ";";
for(i = 0;i <= l1;++i)
{
tMatrix[i][j] = fMatrix[i][j] + rMatrix[i][j];
std::cout << tMatrix[i][j] << ";";
}
std::cout << std::endl;
}
}
#endif
// ----------------------------------------------------------------------------
// Function _printBinary()
// ----------------------------------------------------------------------------
// Debug integer types in binary format.
template <typename TStream, typename T>
inline void
_printBinary(TStream & stream, T const n)
{
std::bitset<BitsPerValue<T>::VALUE> bits(n);
stream << bits;
stream << '\n';
}
// ----------------------------------------------------------------------------
// Function globalAlignment()
// ----------------------------------------------------------------------------
// When using different alphabets, we will internally use the pattern alphabet
// for the comparison. This means that the text character is converted to the
// pattern alphabet. Here, the "pattern" is the shorter source sequence.
template <typename TSequenceH, typename TGapsSpecH, typename TSequenceV, typename TGapsSpecV>
int
_globalAlignment(Gaps<TSequenceH, TGapsSpecH> & gapsH,
Gaps<TSequenceV, TGapsSpecV> & gapsV,
MyersHirschberg const & algorithmTag)
{
// Switch horizontal and vertical gap roles, gapsV should be the shorter one
// to fit into less words.
if (length(source(gapsH)) < length(source(gapsV)))
return _globalAlignment(gapsV, gapsH, algorithmTag);
clearGaps(gapsH);
clearGaps(gapsV);
clearClipping(gapsH);
clearClipping(gapsV);
typedef int TScoreValue;
// use size of unsigned int as blocksize for bit-vectors
const unsigned int BLOCK_SIZE = BitsPerValue<unsigned int>::VALUE;
// saves the score value that will be returned
TScoreValue score,total_score = 0;
typedef typename Value<TSequenceV>::Type TPatternAlphabet;
typedef typename Size<TSequenceH>::Type TStringSize;
typedef typename Iterator<TSequenceH const, Rooted>::Type TSequenceHIterator;
typedef typename Iterator<TSequenceV const, Rooted>::Type TSequenceVIterator;
typedef Gaps<TSequenceH, TGapsSpecH> TGapsH;
typedef Gaps<TSequenceV, TGapsSpecV> TGapsV;
typedef typename Iterator<TGapsH, Rooted>::Type TGapsHIterator;
typedef typename Iterator<TGapsV, Rooted>::Type TGapsVIterator;
typedef typename Iterator<Matrix<TScoreValue>, Rooted>::Type TMatrixIterator;
TGapsHIterator target_0 = begin(gapsH);
TGapsVIterator target_1 = begin(gapsV);
TSequenceH const & x = source(gapsH);
TSequenceV const & y = source(gapsV);
TStringSize len_x = length(x);
TStringSize len_y = length(y);
// string to store the score values for the currently active cell
String<TScoreValue> c_score;
resize(c_score, len_x + 1, 0);
// scoring-scheme specific score values
TScoreValue score_match = 0;
TScoreValue score_mismatch = -1;
TScoreValue score_gap = -1;
// additional vars
unsigned i;
// stack with parts of matrix that have to be processed
std::stack<HirschbergSet_> to_process;
HirschbergSet_ target;
// myers specific vars and preprocessing
unsigned int patternAlphabetSize = ValueSize<TPatternAlphabet>::VALUE;
unsigned int blockCount = (len_y + BLOCK_SIZE - 1) / BLOCK_SIZE; // maximal count of blocks
String<unsigned> VP;
String<unsigned> VN;
String<unsigned> forwardBitMask;
String<unsigned> reverseBitMask;
resize(VP, blockCount, std::numeric_limits<unsigned>::max());
resize(VN, blockCount, 0);
// first bitMask will be constructed from the shorter sequence
resize(forwardBitMask, patternAlphabetSize * blockCount, 0);
resize(reverseBitMask, patternAlphabetSize * blockCount, 0);
// encoding the letters as bit-vectors
for (unsigned int j = 0; j < len_y; j++){
forwardBitMask[blockCount * ordValue(getValue(y,j)) + j/BLOCK_SIZE] = forwardBitMask[blockCount * ordValue(getValue(y,j)) + j/BLOCK_SIZE] | 1 << (j%BLOCK_SIZE);
reverseBitMask[blockCount * ordValue(getValue(y,len_y - j - 1)) + j/BLOCK_SIZE] = reverseBitMask[blockCount * ordValue(getValue(y,len_y - j - 1)) + j/BLOCK_SIZE] | 1 << (j%BLOCK_SIZE);
}
HirschbergSet_ hs_complete{0, static_cast<unsigned>(len_x), 0, static_cast<unsigned>(len_y), 1};
to_process.push(hs_complete);
while(!to_process.empty())
{
target = to_process.top();
to_process.pop();
/* if score is zero, the whole part of the sequence can be simply skipped */
if(_score(target) == 0)
{
/* coukd work faster */
for(i = 0;i < (_end1(target) - _begin1(target));++i)
{
++target_0;
++target_1;
}
#ifdef MYERS_HIRSCHBERG_VERBOSE
printf("skipped %i to %i in first sequence\n",_begin1(target),_end1(target));
#endif
}
else if(_begin1(target) == _end1(target))
{
#ifdef MYERS_HIRSCHBERG_VERBOSE
std::cout << "align y " << _begin2(target) << " to " << _end2(target) << std::endl;
std::cout << "align " << infix(y,_begin2(target),_end2(target)) << std::endl << std::endl;
#endif
for(i = 0;i < (_end2(target) - _begin2(target));++i)
{
insertGap(target_0);
++target_0;
++target_1;
}
}
else if(_begin2(target) + 1 == _end2(target))
{
/* ALIGN */
#ifdef MYERS_HIRSCHBERG_VERBOSE
std::cout << "align x " << _begin1(target) << " to " << _end1(target) << " and y " << _begin2(target) << " to " << _end2(target) << std::endl;
std::cout << "align " << infix(x,_begin1(target),_end1(target)) << " and " << infix(y,_begin2(target),_end2(target)) << std::endl << std::endl;
#endif
TStringSize len_1 = _end1(target) - _begin1(target);
TStringSize len_2 = _end2(target) - _begin2(target);
Matrix<TScoreValue> matrix_;
setDimension(matrix_, 2);
setLength(matrix_, 0, len_1 + 1);
setLength(matrix_, 1, len_2 + 1);
resize(matrix_);
/* init matrix */
TSequenceHIterator xs_begin = iter(x,_begin1(target)) - 1;
TSequenceHIterator xs_end = iter(x,_end1(target)) - 1;
TSequenceVIterator ys_begin = iter(y,_begin2(target)) - 1;
TSequenceVIterator ys_end = iter(y,_end2(target)) - 1;
TSequenceHIterator xs = xs_end;
TSequenceVIterator ys;
TMatrixIterator col_ = end(matrix_) - 1;
TMatrixIterator finger1;
TMatrixIterator finger2;
TScoreValue h = 0;
TScoreValue border_ = score_gap;
TScoreValue v = border_;
//-------------------------------------------------------------------------
// init
finger1 = col_;
*finger1 = 0;
for (xs = xs_end; xs != xs_begin; --xs)
{
goPrevious(finger1, 0);
*finger1 = border_;
border_ += score_gap;
}
//-------------------------------------------------------------------------
//fill matrix
border_ = 0;
for (ys = ys_end; ys != ys_begin; --ys)
{
TPatternAlphabet cy = *ys;
h = border_;
border_ += score_gap;
v = border_;
finger2 = col_;
goPrevious(col_, 1);
finger1 = col_;
*finger1 = v;
for (xs = xs_end; xs != xs_begin; --xs)
{
goPrevious(finger1, 0);
goPrevious(finger2, 0);
if (*xs == cy)
{
v = h + score_match;
h = *finger2;
}
else
{
TScoreValue s1 = h + score_mismatch;
h = *finger2;
TScoreValue s2 = score_gap + ((h > v) ? h : v);
v = (s1 > s2) ? s1 : s2;
}
*finger1 = v;
}
}
// if computed the whole matrix last value of v = alignment score
if(target == hs_complete) total_score = v;
/* TRACE BACK */
finger1 = begin(matrix_);
xs = iter(x,_begin1(target));
ys = iter(y,_begin2(target));
xs_end = iter(x,_end1(target));
ys_end = iter(y,_end2(target));
while ((xs != xs_end) && (ys != ys_end))
{
bool gv;
bool gh;
if (*xs == *ys)
{
gv = gh = true;
}
else
{
TMatrixIterator it_ = finger1;
goNext(it_, 0);
TScoreValue v = *it_;
goNext(it_, 1);
TScoreValue d = *it_;
it_ = finger1;
goNext(it_, 1);
TScoreValue h = *it_;
gv = (v >= h) | (d >= h);
gh = (h >= v) | (d >= v);
}
if (gv)
{
++xs;
goNext(finger1, 0);
}
else
{
insertGap(target_0);
}
if (gh)
{
++ys;
goNext(finger1, 1);
}
else
{
insertGap(target_1);
}
++target_0;
++target_1;
}
// if x or y did not reached there end position, fill the rest with gaps
while(xs != xs_end)
{
insertGap(target_1);
++target_0;
++target_1;
++xs;
}
while(ys != ys_end)
{
insertGap(target_0);
++target_0;
++target_1;
++ys;
}
/* END ALIGN */
#ifdef MYERS_HIRSCHBERG_VERBOSE
std::cout << std::endl << align_ << std::endl << std::endl;
#endif
}
else
{
/*
---------------------------------------------------------------
Calculate cut position using extended Myers-Bitvector-Algorithm
---------------------------------------------------------------
*/
/* declare variables */
unsigned int X, D0, HN, HP;
/* compute cut position */
unsigned mid = static_cast<int>(floor( static_cast<double>((_begin2(target) + _end2(target))/2) ));
/* debug infos */
#ifdef MYERS_HIRSCHBERG_VERBOSE
std::cout << "calculate cut for x " << _begin1(target) << " to " << _end1(target) << " and y " << _begin2(target) << " to " << _end2(target) << std::endl;
std::cout << "calculate cut for " << infix(x,_begin1(target),_end1(target)) << " and " << infix(y,_begin2(target),_end2(target)) << std::endl;
std::cout << "cut is in row " << mid << " symbol is " << getValue(x,mid-1) << std::endl << std::endl;
std::cout << std::endl;
_writeDebugMatrix(infix(x,_begin1(target),_end1(target)),infix(y,_begin2(target),_end2(target)));
std::cout << std::endl;
#endif
/* compute blocks and score masks */
unsigned fStartBlock = _begin2(target) / BLOCK_SIZE;
unsigned fEndBlock = (mid - 1) / BLOCK_SIZE;
unsigned fSpannedBlocks = (fEndBlock - fStartBlock) + 1;
unsigned int fScoreMask = 1 << ((mid - 1) % BLOCK_SIZE);
unsigned int fOffSet = _begin2(target) % BLOCK_SIZE;
unsigned int fSilencer = ~0;
fSilencer <<= fOffSet;
/* reset v-bitvectors */
std::fill(begin(VP, Standard()) + fStartBlock, begin(VP, Standard()) + fEndBlock + 1, std::numeric_limits<unsigned>::max());
std::fill(begin(VN, Standard()) + fStartBlock, begin(VN, Standard()) + fEndBlock + 1, 0);
/* determine start-position and start-score */
auto pos = _begin1(target);
score = (mid - _begin2(target)) * score_gap;
c_score[pos] = score;
/* compute with myers - forward - begin */
if(fSpannedBlocks == 1)
{
while (pos < _end1(target)) {
X = (fSilencer & forwardBitMask[(blockCount * ordValue(static_cast<TPatternAlphabet>(getValue(x,pos)))) + fStartBlock]) | VN[fStartBlock];
D0 = ((VP[fStartBlock] + (X & VP[fStartBlock])) ^ VP[fStartBlock]) | X;
HN = VP[fStartBlock] & D0;
HP = VN[fStartBlock] | ~(VP[fStartBlock] | D0);
X = (HP << 1) | (1 << fOffSet);
VN[fStartBlock] = X & D0;
VP[fStartBlock] = (HN << 1) | ~(X | D0);
if (HP & fScoreMask)
score--;
else if (HN & fScoreMask)
score++;
c_score[pos + 1] = score;
++pos;
}
} /* end - short patten */
else
{
unsigned shift, currentBlock;
unsigned int temp, carryD0, carryHP, carryHN;
while (pos < _end1(target))
{
carryD0 = carryHP = carryHN = 0;
shift = blockCount * ordValue(static_cast<TPatternAlphabet>(getValue(x,pos)));
// computing first the top most block
X = (fSilencer & forwardBitMask[shift + fStartBlock]) | VN[fStartBlock];
temp = VP[fStartBlock] + (X & VP[fStartBlock]);
carryD0 = temp < VP[fStartBlock];
D0 = (temp ^ VP[fStartBlock]) | X;
HN = VP[fStartBlock] & D0;
HP = VN[fStartBlock] | ~(VP[fStartBlock] | D0);
X = (HP << 1) | (1 << fOffSet);
carryHP = HP >> (BLOCK_SIZE - 1);
VN[fStartBlock] = X & D0;
temp = (HN << 1);
carryHN = HN >> (BLOCK_SIZE - 1);
VP[fStartBlock] = temp | ~(X | D0);
// compute the remaining blocks
for (currentBlock = fStartBlock + 1; currentBlock <= fEndBlock; currentBlock++) {
X = forwardBitMask[shift + currentBlock] | VN[currentBlock];
temp = VP[currentBlock] + (X & VP[currentBlock]) + carryD0;
carryD0 = ((carryD0) ? temp <= VP[currentBlock] : temp < VP[currentBlock]);
D0 = (temp ^ VP[currentBlock]) | X;
HN = VP[currentBlock] & D0;
HP = VN[currentBlock] | ~(VP[currentBlock] | D0);
X = (HP << 1) | carryHP;
carryHP = HP >> (BLOCK_SIZE-1);
VN[currentBlock] = X & D0;
temp = (HN << 1) | carryHN;
carryHN = HN >> (BLOCK_SIZE - 1);
VP[currentBlock] = temp | ~(X | D0);
}
/* update score */
if (HP & fScoreMask)
score--;
else if (HN & fScoreMask)
score++;
c_score[pos + 1] = score;
++pos;
}
} /* end - long patten */
/* compute with myers - forward - end */
/* compute blocks and score masks */
unsigned rStartBlock = (len_y - _end2(target)) / BLOCK_SIZE;
unsigned rEndBlock = (len_y - mid - 1) / BLOCK_SIZE;
unsigned rSpannedBlocks = (rEndBlock - rStartBlock) + 1;
unsigned int rScoreMask = 1 << ((len_y - mid - 1) % BLOCK_SIZE);
unsigned int rOffSet = (len_y - _end2(target)) % BLOCK_SIZE;
unsigned int rSilencer = ~0;
rSilencer <<= rOffSet;
/* reset v-bitvectors */
std::fill(begin(VP, Standard()) + rStartBlock, begin(VP, Standard()) + rEndBlock + 1, std::numeric_limits<unsigned>::max());
std::fill(begin(VN, Standard()) + rStartBlock, begin(VN, Standard()) + rEndBlock + 1, 0);
/* determine start-position and start-score */
pos = _end1(target);
score = (_end2(target) - mid) * score_gap;
/* set start score */
c_score[_end1(target)] += score;
/* determine optimal cut position -- score extension */
TScoreValue max = c_score[_end1(target)];
TScoreValue rmax = score;
unsigned int pos_max = _end1(target);
/* compute with myers - reverse - begin */
if(rSpannedBlocks == 1)
{
while (pos-- > _begin1(target)) {
X = (rSilencer & reverseBitMask[(blockCount * ordValue(static_cast<TPatternAlphabet>(getValue(x,pos)))) + rStartBlock]) | VN[rStartBlock];
D0 = ((VP[rStartBlock] + (X & VP[rStartBlock])) ^ VP[rStartBlock]) | X;
HN = VP[rStartBlock] & D0;
HP = VN[rStartBlock] | ~(VP[rStartBlock] | D0);
X = (HP << 1) | (1 << rOffSet);
VN[rStartBlock] = X & D0;
VP[rStartBlock] = (HN << 1) | ~(X | D0);
if (HP & rScoreMask)
--score;
else if (HN & rScoreMask)
++score;
c_score[pos] += score;
/* check for optimality -- score extension */
if(c_score[pos]> max)
{
pos_max = pos;
max = c_score[pos];
rmax = score;
}
}
} /* end - short pattern */
else
{
unsigned shift, currentBlock;
unsigned int temp, carryD0, carryHP, carryHN;
while (pos-- > _begin1(target))
{
carryD0 = carryHP = carryHN = 0;
shift = blockCount * ordValue(static_cast<TPatternAlphabet>(getValue(x,pos)));
// compute first the top most block
X = (rSilencer & reverseBitMask[shift + rStartBlock]) | VN[rStartBlock];
temp = VP[rStartBlock] + (X & VP[rStartBlock]);
carryD0 = temp < VP[rStartBlock];
D0 = (temp ^ VP[rStartBlock]) | X;
HN = VP[rStartBlock] & D0;
HP = VN[rStartBlock] | ~(VP[rStartBlock] | D0);
X = (HP << 1) | (1 << rOffSet);
carryHP = HP >> (BLOCK_SIZE - 1);
VN[rStartBlock] = X & D0;
temp = (HN << 1);
carryHN = HN >> (BLOCK_SIZE - 1);
VP[rStartBlock] = temp | ~(X | D0);
// compute the remaining blocks
for (currentBlock = rStartBlock + 1; currentBlock <= rEndBlock; currentBlock++) {
X = reverseBitMask[shift + currentBlock] | VN[currentBlock];
temp = VP[currentBlock] + (X & VP[currentBlock]) + carryD0;
carryD0 = ((carryD0) ? temp <= VP[currentBlock] : temp < VP[currentBlock]);
D0 = (temp ^ VP[currentBlock]) | X;
HN = VP[currentBlock] & D0;
HP = VN[currentBlock] | ~(VP[currentBlock] | D0);
X = (HP << 1) | carryHP;
carryHP = HP >> (BLOCK_SIZE-1);
VN[currentBlock] = X & D0;
temp = (HN << 1) | carryHN;
carryHN = HN >> (BLOCK_SIZE - 1);
VP[currentBlock] = temp | ~(X | D0);
}
if (HP & rScoreMask)
--score;
else if (HN & rScoreMask)
++score;
c_score[pos] += score;
/* check for optimality -- score extension*/
if(c_score[pos] > max)
{
pos_max = pos;
max = c_score[pos];
rmax = score;
}
}
} /* end - long pattern */
/* compute with myers - reverse - end */
// if computed the whole matrix max = alignment score
if(target == hs_complete)
total_score = max;
#ifdef MYERS_HIRSCHBERG_VERBOSE
printf("Optimal cut is at %i and %i with forward score %i and reverse score %i\n\n",mid,pos_max,(max - rmax),rmax);
#endif
/* push the two computed parts of the dp-matrix on process stack */
to_process.push(HirschbergSet_{pos_max, _end1(target), mid, _end2(target), rmax});
to_process.push(HirschbergSet_{_begin1(target), pos_max, _begin2(target), mid, max - rmax});
}
/* END CUT */
}
return total_score;
}
} // namespace seqan
#endif // #ifndef SEQAN_INCLUDE_SEQAN_ALIGN_GLOBAL_ALIGNMENT_MYERS_HIRSCHBERG_IMPL_H_
