void operator() (const state_type rhot, double t) const
{
// Find dimension of density matric from vector.
int side = int(sqrt(float(rhot.size())));
// Grab elements corresponding to diagonals in density matrix.
const vector_slice<const state_type> diags(rhot, slice(0,side+1,side));
// Print diagonal elements.
m_out << t;
for(size_t n = 0; n < diags.size(); n++) m_out << "\t" << diags[n].real();
m_out << "\t" << sum(diags).real();
m_out << endl;
}
void copy(vector_slice<vector<SCALARTYPE> > const & gpu_vector_slice,
VectorType & cpu_vector)
{
assert(gpu_vector_slice.end() - gpu_vector_slice.begin() >= 0 && bool("Range must have nonnegative length!"));
if (gpu_vector_slice.end() - gpu_vector_slice.begin() > 0)
{
std::vector<SCALARTYPE> temp_buffer(gpu_vector_slice.stride() * gpu_vector_slice.size());
viennacl::backend::memory_read(gpu_vector_slice.handle(), sizeof(SCALARTYPE)*gpu_vector_slice.start(), sizeof(SCALARTYPE)*temp_buffer.size(), &(temp_buffer[0]));
for (vcl_size_t i=0; i<cpu_vector.size(); ++i)
cpu_vector[i] = temp_buffer[i * gpu_vector_slice.stride()];
}
}
void copy(const VectorType & cpu_vector,
vector_slice<vector<SCALARTYPE> > & gpu_vector_slice )
{
if (cpu_vector.size() > 0)
{
std::vector<SCALARTYPE> temp_buffer(gpu_vector_slice.stride() * gpu_vector_slice.size());
viennacl::backend::memory_read(gpu_vector_slice.handle(), sizeof(SCALARTYPE)*gpu_vector_slice.start(), sizeof(SCALARTYPE)*temp_buffer.size(), &(temp_buffer[0]));
for (vcl_size_t i=0; i<cpu_vector.size(); ++i)
temp_buffer[i * gpu_vector_slice.stride()] = cpu_vector[i];
viennacl::backend::memory_write(gpu_vector_slice.handle(), sizeof(SCALARTYPE)*gpu_vector_slice.start(), sizeof(SCALARTYPE)*temp_buffer.size(), &(temp_buffer[0]));
}
}
vector_slice(vector_slice<VectorType> const & v, slice const & entry_slice)
: base_type(const_cast<handle_type &>(v.handle()),
entry_slice.size(), v.start() + v.stride() * entry_slice.start(), entry_slice.stride() * v.stride()) {}
