Ipp32f EuclidianDistance<Ipp32f>::doCalculate(const VectorT<Ipp32f>& v1, const VectorT<Ipp32f>& v2) const {
if(v1.size()!=v2.size())
fthrow(Exception, "Input vectors must have the same size.");
Ipp32f dist = 0;
#ifdef NICE_USELIB_IPP
VectorT<Ipp32f> res(v1.size());
ippsSub_32f(v1.getDataPointer(), v2.getDataPointer(), res.getDataPointer(), v1.size());
ippsSqr_32f(res.getDataPointer(), res.getDataPointer(), res.size());
dist = res.Sum();
#else // NICE_USELIB_IPP
const Ipp32f* pSrc1 = v1.getDataPointer();
const Ipp32f* pSrc2 = v2.getDataPointer();
for(Ipp32u i=0; i<v1.size(); ++i,++pSrc1,++pSrc2)
dist += (*pSrc1-*pSrc2)*(*pSrc1-*pSrc2);
#endif // NICE_USELIB_IPP
dist = std::sqrt(dist);
return dist;
}
Ipp32f BhattacharyyaDistance<Ipp32f>::doCalculate(const VectorT<Ipp32f>& v1, const VectorT<Ipp32f>& v2) const {
if(v1.size()!=v2.size())
fthrow(Exception, "Input vectors must have the same size.");
Ipp32f B;
#ifdef NICE_USELIB_IPP
VectorT<Ipp32f> v1f(v1);
v1f *= v2;
ippsSqrt(v1f.getDataPointer(), v1f.getDataPointer(), v1f.size());
ippsSum(v1f.getDataPointer(), v1f.size(), &B);
#else // NICE_USELIB_IPP
B = 0.0;
for(uint i=0; i<v1.size(); ++i)
B += std::sqrt(v1[i]*v2[i]);
#endif // NICE_USELIB_IPP
return std::sqrt(1-B);
}
void vector_test(const VectorT& A, const VectorT& B, Accumulator& Result)
{
const Uint sizeA = A.size();
const Uint sizeB = B.size();
for(Uint i = 0, j = 0; i != sizeA && j != sizeB; ++i, ++j)
test(A[i], B[j], Result);
Result.exact(sizeA == sizeB);
};
void set_row(const Uint array_idx, const VectorT& row)
{
if (row.size() != row_size(array_idx))
m_array[array_idx].resize(row.size());
Uint j=0;
boost_foreach( const typename VectorT::value_type& v, row)
m_array[array_idx][j++] = v;
}
void set_row(const Uint array_idx, const VectorT& row)
{
cf3_assert(row.size() == row_size());
Row row_to_set = m_array[array_idx];
for(Uint j=0; j<row.size(); ++j)
row_to_set[j] = row[j];
}
MatrixT diag(VectorT const &v,
typename MatrixT::ScalarType zero =
static_cast<typename MatrixT::ScalarType>(0))
{
MatrixT diag(v.size(), v.size(), zero);
diag.set_zero(zero);
//populate diagnals:
std::vector<IndexType> indices;
for (graphblas::IndexType ix = 0; ix < v.size(); ++ix) {
indices.push_back(ix);
}
graphblas::buildmatrix(diag, indices.begin(), indices.begin(), v.begin(), v.size());
return diag;
}
void
check_v(
VectorT vec,
IndexObj const& obj)
{
for (index_type p=0; p<vec.size(); ++p)
test_assert(vec(p) == obj(p));
}
void
set_v(
VectorT vec,
IndexObj const& obj)
{
for (index_type p=0; p<vec.size(); ++p)
vec(p) = obj(p);
}
void print_vector(StreamT& stream, const VectorT& vector, const std::string& sep=" ", const std::string& prefix = "", const std::string& suffix = "")
{
stream << prefix;
const Uint vector_size = vector.size();
for(Uint i = 0; i != vector_size; ++i)
{
stream << (i != 0 ? sep : "") << vector[i];
}
stream << suffix;
}
typename VectorT::value_type
norm_2(VectorT const& v1,
typename viennacl::tools::enable_if< viennacl::is_stl< typename viennacl::traits::tag_of< VectorT >::type >::value
>::type* dummy = 0)
{
//std::cout << "stl .. " << std::endl;
typename VectorT::value_type result = 0;
for (typename VectorT::size_type i=0; i<v1.size(); ++i)
result += v1[i] * v1[i];
return sqrt(result);
}
void FilterT<float,float,float>::filterX ( const ImageT<float>& src, const VectorT<float>& kernel, ImageT<float> &result, const int& anchor )
{
if ( result.width() != src.width() || result.height() != src.height() )
{
result = ImageT<float> ( src.width(), src.height() );
}
uint kernelanch = ( anchor < 0 ) ? ( kernel.size() / 2 ) : anchor;
#ifdef NICE_USELIB_IPP
IppiSize ippiSize = {(int)(src.width() - ( kernel.size() - 1 )), (int)(src.height()) };
IppStatus ret = ippiFilterRow_C1R ( src.getPixelPointerXY ( kernel.size() - 1 - kernelanch, 0 ),
src.getStepsize(),
result.getPixelPointerXY ( kernelanch, 0 ),
result.getStepsize(),
ippiSize, kernel.getDataPointer(), kernel.size(), kernelanch );
if ( ret != ippStsNoErr )
fthrow ( ImageException, ippGetStatusString ( ret ) );
#else // NICE_USELIB_IPP
double sum = 0.0;
int ka = kernelanch + 1;
uint xstart = kernelanch;
uint xend = src.width() - ( kernel.size() - 1 - kernelanch );
int i;
const float* pSrc;
float* pDst;
for ( int y = 0; y < src.height(); ++y )
{
pSrc = src.getPixelPointerXY ( kernelanch, y );
pDst = result.getPixelPointerXY ( kernelanch, y );
for ( uint x = xstart; x < xend; ++x, ++pSrc, ++pDst ) {
sum = 0.0;
i = kernel.size();
do {
sum += * ( pSrc - ka + i ) * kernel[kernel.size()-i];
--i;
} while ( i != 0 );
*pDst = static_cast<float> ( sum );
}
}
#endif // NICE_USELIB_IPP
}
void FilterT<float,float,float>::filterY ( const ImageT<float>& src, const VectorT<float>& kernel, ImageT<float> &result, const int& anchor )
{
if(result.width() != src.width() || result.height() != src.height())
{
result = ImageT<float>(src.width(), src.height());
}
uint kernelanch = ( anchor < 0 ) ? ( kernel.size() / 2 ) : anchor;
#ifdef NICE_USELIB_IPP
IppiSize ippiSize = {(int)(src.width()), (int)(src.height() - ( kernel.size() - 1 )) };
IppStatus ret = ippiFilterColumn_C1R ( src.getPixelPointerXY ( 0, kernel.size() - 1 - kernelanch ),
src.getStepsize(),
result.getPixelPointerXY ( 0, kernelanch ),
result.getStepsize(),
ippiSize, kernel.getDataPointer(), kernel.size(), kernelanch );
if ( ret != ippStsNoErr )
fthrow ( ImageException, ippGetStatusString ( ret ) );
#else // NICE_USELIB_IPP*/
double sum = 0.0;
int ks = kernel.size() - 1;
int i;
for ( uint y = kernelanch; y < src.height() - ( kernel.size() - 1 - kernelanch ); ++y )
{
for ( int x = 0; x < src.width(); ++x ) {
sum = 0.0;
i = ks;
do {
//TODO: optimizable similar to filterX, old version was buggy
sum += src(x,y+kernelanch-ks+i) * kernel[ks-i];
--i;
} while ( i >= 0 );
result(x,y) = static_cast<float> ( sum );
}
}
#endif // NICE_USELIB_IPP
}
std::vector<
typename viennacl::result_of::cpu_value_type<typename VectorT::value_type>::type
>
bisect(VectorT const & alphas, VectorT const & betas)
{
typedef typename viennacl::result_of::value_type<VectorT>::type ScalarType;
typedef typename viennacl::result_of::cpu_value_type<ScalarType>::type CPU_ScalarType;
std::size_t size = betas.size();
std::vector<CPU_ScalarType> x_temp(size);
std::vector<CPU_ScalarType> beta_bisect;
std::vector<CPU_ScalarType> wu;
double rel_error = std::numeric_limits<CPU_ScalarType>::epsilon();
beta_bisect.push_back(0);
for(std::size_t i = 1; i < size; i++){
beta_bisect.push_back(betas[i] * betas[i]);
}
double xmin = alphas[size - 1] - std::fabs(betas[size - 1]);
double xmax = alphas[size - 1] + std::fabs(betas[size - 1]);
for(std::size_t i = 0; i < size - 1; i++)
{
double h = std::fabs(betas[i]) + std::fabs(betas[i + 1]);
if (alphas[i] + h > xmax)
xmax = alphas[i] + h;
if (alphas[i] - h < xmin)
xmin = alphas[i] - h;
}
double eps1 = 1e-6;
/*double eps2 = (xmin + xmax > 0) ? (rel_error * xmax) : (-rel_error * xmin);
if(eps1 <= 0)
eps1 = eps2;
else
eps2 = 0.5 * eps1 + 7.0 * eps2; */
double x0 = xmax;
for(std::size_t i = 0; i < size; i++)
{
x_temp[i] = xmax;
wu.push_back(xmin);
}
for(long k = size - 1; k >= 0; --k)
{
double xu = xmin;
for(long i = k; i >= 0; --i)
{
if(xu < wu[k-i])
{
xu = wu[i];
break;
}
}
if(x0 > x_temp[k])
x0 = x_temp[k];
double x1 = (xu + x0) / 2.0;
while (x0 - xu > 2.0 * rel_error * (std::fabs(xu) + std::fabs(x0)) + eps1)
{
std::size_t a = 0;
double q = 1;
for(std::size_t i = 0; i < size; i++)
{
if(q != 0)
q = alphas[i] - x1 - beta_bisect[i] / q;
else
q = alphas[i] - x1 - std::fabs(betas[i] / rel_error);
if(q < 0)
a++;
}
if (a <= static_cast<std::size_t>(k))
{
xu = x1;
if(a < 1)
wu[0] = x1;
else
{
wu[a] = x1;
if(x_temp[a - 1] > x1)
x_temp[a - 1] = x1;
}
}
else
x0 = x1;
x1 = (xu + x0) / 2.0;
}
x_temp[k] = x1;
}
return x_temp;
}
void operator()(SystemType pde_system,
DomainType & domain,
MatrixT & system_matrix,
VectorT & load_vector
) const
{
typedef typename viennagrid::result_of::cell_tag<DomainType>::type CellTag;
typedef typename viennagrid::result_of::point<DomainType>::type PointType;
typedef typename viennagrid::result_of::element<DomainType, CellTag>::type CellType;
typedef typename viennagrid::result_of::element_range<DomainType, CellTag>::type CellContainer;
typedef typename viennagrid::result_of::iterator<CellContainer>::type CellIterator;
typedef typename SystemType::equation_type EquationType;
#ifdef VIENNAFEM_DEBUG
std::cout << "Strong form: " << pde_system.pde(0) << std::endl;
#endif
log_strong_form(pde_system);
EquationType weak_form_general = viennafem::make_weak_form(pde_system.pde(0));
#ifdef VIENNAFEM_DEBUG
std::cout << "* pde_solver::operator(): Using weak form general: " << weak_form_general << std::endl;
#endif
std::vector<EquationType> temp(1); temp[0] = weak_form_general;
log_weak_form(temp, pde_system);
EquationType weak_form = viennamath::apply_coordinate_system(viennamath::cartesian< PointType::dim >(), weak_form_general);
//EquationType weak_form = viennamath::apply_coordinate_system(viennamath::cartesian<Config::coordinate_system_tag::dim>(), weak_form_general);
temp[0] = weak_form;
log_coordinated_weak_form(temp, pde_system);
#ifdef VIENNAFEM_DEBUG
std::cout << "* pde_solver::operator(): Using weak form " << weak_form << std::endl;
std::cout << "* pde_solver::operator(): Write dt_dx coefficients" << std::endl;
#endif
typedef typename reference_cell_for_basis<CellTag, viennafem::lagrange_tag<1> >::type ReferenceCell;
//
// Create accessors for performance in the subsequent dt_dx_handler step
//
//viennafem::dtdx_assigner<DomainType, StorageType, ReferenceCell>::apply(domain, storage);
viennafem::dt_dx_handler<DomainType, StorageType, ReferenceCell> dt_dx_handler(domain, storage);
//fill with cell quantities
CellContainer cells = viennagrid::elements<CellType>(domain);
for (CellIterator cell_iter = cells.begin();
cell_iter != cells.end();
++cell_iter)
{
//cell_iter->print_short();
//viennadata::access<example_key, double>()(*cell_iter) = i;
//viennafem::dt_dx_handler<ReferenceCell>::apply(storage, *cell_iter);
dt_dx_handler(*cell_iter);
}
#ifdef VIENNAFEM_DEBUG
std::cout << "* pde_solver::operator(): Create Mapping:" << std::endl;
#endif
std::size_t map_index = create_mapping(storage, pde_system, domain);
#ifdef VIENNAFEM_DEBUG
std::cout << "* pde_solver::operator(): Assigned degrees of freedom in domain so far: " << map_index << std::endl;
#endif
// resize global system matrix and load vector if needed:
// TODO: This can be a performance bottleneck for large numbers of segments! (lots of resize operations...)
if (map_index > system_matrix.size1())
{
MatrixT temp = system_matrix;
////std::cout << "Resizing system matrix..." << std::endl;
system_matrix.resize(map_index, map_index, false);
system_matrix.clear();
system_matrix.resize(map_index, map_index, false);
for (typename MatrixT::iterator1 row_it = temp.begin1();
row_it != temp.end1();
++row_it)
{
for (typename MatrixT::iterator2 col_it = row_it.begin();
col_it != row_it.end();
++col_it)
system_matrix(col_it.index1(), col_it.index2()) = *col_it;
}
}
if (map_index > load_vector.size())
{
VectorT temp = load_vector;
#ifdef VIENNAFEM_DEBUG
std::cout << "Resizing load vector..." << std::endl;
#endif
load_vector.resize(map_index, false);
load_vector.clear();
load_vector.resize(map_index, false);
for (std::size_t i=0; i<temp.size(); ++i)
load_vector(i) = temp(i);
}
#ifdef VIENNAFEM_DEBUG
std::cout << "* pde_solver::operator(): Transform to reference element" << std::endl;
#endif
EquationType transformed_weak_form = viennafem::transform_to_reference_cell<CellType>(storage, weak_form, pde_system);
temp[0] = transformed_weak_form;
log_transformed_weak_form<CellType, StorageType>(temp, pde_system);
std::cout << "* pde_solver::operator(): Transformed weak form:" << std::endl;
std::cout << transformed_weak_form << std::endl;
//std::cout << std::endl;
#ifdef VIENNAFEM_DEBUG
std::cout << "* pde_solver::operator(): Assemble system" << std::endl;
#endif
typedef detail::equation_wrapper<MatrixT, VectorT> wrapper_type;
wrapper_type wrapper(system_matrix, load_vector);
detail::pde_assembler_internal()(storage, transformed_weak_form, pde_system, domain, wrapper);
// pde_assembler_internal()(transformed_weak_form, pde_system, domain, system_matrix, load_vector);
}
std::vector<int> flatnonzero(const VectorT& x) {
std::vector<int> out;
for (int i=0; i < x.size(); ++i) if (x[i] != 0) out.push_back(i);
return out;
}
// construct table from length vector
template <typename VectorT> explicit RangeTable(const VectorT &lengths)
{
const unsigned number_of_blocks = [&lengths]()
{
unsigned num = (lengths.size() + 1) / (BLOCK_SIZE + 1);
if ((lengths.size() + 1) % (BLOCK_SIZE + 1) != 0)
{
num += 1;
}
return num;
}();
block_offsets.reserve(number_of_blocks);
diff_blocks.reserve(number_of_blocks);
unsigned last_length = 0;
unsigned lengths_prefix_sum = 0;
unsigned block_idx = 0;
unsigned block_counter = 0;
BlockT block;
unsigned block_sum = 0;
for (const unsigned l : lengths)
{
// first entry of a block: encode absolute offset
if (block_idx == 0)
{
block_offsets.push_back(lengths_prefix_sum);
block_sum = 0;
}
else
{
block[block_idx - 1] = last_length;
block_sum += last_length;
}
BOOST_ASSERT((block_idx == 0 && block_offsets[block_counter] == lengths_prefix_sum) ||
lengths_prefix_sum == (block_offsets[block_counter] + block_sum));
// block is full
if (BLOCK_SIZE == block_idx)
{
diff_blocks.push_back(block);
block_counter++;
}
// we can only store strings with length 255
BOOST_ASSERT(l <= 255);
lengths_prefix_sum += l;
last_length = l;
block_idx = (block_idx + 1) % (BLOCK_SIZE + 1);
}
// Last block can't be finished because we didn't add the sentinel
BOOST_ASSERT(block_counter == (number_of_blocks - 1));
// one block missing: starts with guard value
if (0 == block_idx)
{
// the last value is used as sentinel
block_offsets.push_back(lengths_prefix_sum);
block_idx = 1;
last_length = 0;
}
while (0 != block_idx)
{
block[block_idx - 1] = last_length;
last_length = 0;
block_idx = (block_idx + 1) % (BLOCK_SIZE + 1);
}
diff_blocks.push_back(block);
BOOST_ASSERT(diff_blocks.size() == number_of_blocks &&
block_offsets.size() == number_of_blocks);
sum_lengths = lengths_prefix_sum;
}
