//pb with convolution: regarder les pixels à l'intérieurs de la matrice. Affichage ligne 36. Travailler sur a qui semble etre nul trop souvent.
void Convolution(boost::multi_array<unsigned char,2> &input,
boost::multi_array<unsigned char,2> &output,
boost::multi_array<float,2> &kernel){
if (input.shape()[0]==output.shape()[0] and input.shape()[1]==output.shape()[1]
and kernel.shape()[0]== kernel.shape()[1] and kernel.shape()[0]%2==1
and kernel.shape()[0]>=3 ){
int k0 =int(kernel.shape()[0]);
int k1 = int(kernel.shape()[1]);
int k = int(floor(double(kernel.shape()[0]/2)));
int row_size = int(output.shape()[0]);
int column_size = int(output.shape()[1]);
boost::multi_array<float,2> a(boost::extents[2*k+row_size][2*k+column_size]);
for(int j=0;j<k+1;j++){for(int i=0;i<k+1;i++){a[i][j]=float(input[0][0]);}}
for(int j=0;j<k+1;j++){for(int i=row_size+k-1;i<row_size+2*k;i++){a[i][j]=float(input[row_size-1][0]);}}
for(int j=column_size+k-1;j<column_size+2*k;j++){for(int i=0;i<k+1;i++){a[i][j]=float(input[0][column_size-1]);}}
for(int j=column_size+k-1;j<column_size+2*k;j++){for(int i=row_size+k-1;i<row_size+2*k;i++){a[i][j]=float(input[row_size-1][column_size-1]);}}
for(int j =0;j<k;j++){for(int i=k+1;i<k+row_size-1;i++){a[i][j]=float(input[i-k][k]);}}
for(int j =k+column_size;j<2*k+column_size;j++){for(int i=k+1;i<row_size-1;i++){a[i][j]=float(input[i][column_size-1]);}}//pb
for(int j =k+1;j<k+column_size-1;j++){for(int i=0;i<k;i++){a[i][j]=float(input[k][j-k]);}}
for(int j =k+1;j<k+column_size-1;j++){for(int i=k+row_size;i<2*k+row_size;i++){a[i][j]=float(input[row_size-1][j-k]);}}
for(int j = k+1;j<k+column_size-1;j++){for(int i=k+1;i<k+row_size-1;i++){a[i][j]=float(input[i-k][j-k]);}}
for(int j=k;j<k+column_size;j++){for(int i=k;i<k+row_size;i++){
float p=0;
boost::multi_array<float,2> b(boost::extents[k0][k1]);
for(int r=0;r<k0;r++){for(int s=0; s<k1;s++){
b[r][s]=a[i-k+r][j-k+s];
}}
for(int r=0;r<k0;r++){for(int s=0; s<k1;s++){p=p+b[r][s]*float(kernel[r][s]);}}
if(p<0){p=0;}
if(p>=255){p=255;}
output[i-k][j-k]= static_cast<unsigned char>(lround(p));
}
}
}
else{
std::cout << "Error from the data:" << std::endl;
std::cout << " See the usage of the function convolution" << std::endl;
}
}
/// Copies the contents of the table into the LSS::Vector.
void set( boost::multi_array<Real, 2>& data)
{
cf3_assert(m_is_created);
cf3_assert(data.shape()[0]==m_blockrow_size);
cf3_assert(data.shape()[1]==m_neq);
}
//-----------------------------------------------------------------------------
void MeshPartitioning::build_mesh(Mesh& mesh,
const std::vector<std::size_t>& global_cell_indices,
const boost::multi_array<std::size_t, 2>& cell_global_vertices,
const std::vector<std::size_t>& vertex_indices,
const boost::multi_array<double, 2>& vertex_coordinates,
const std::map<std::size_t, std::size_t>& vertex_global_to_local,
std::size_t tdim, std::size_t gdim, std::size_t num_global_cells,
std::size_t num_global_vertices)
{
Timer timer("PARALLEL 3: Build mesh (from local mesh data)");
// Get number of processes and process number
const std::size_t num_processes = MPI::num_processes();
const std::size_t process_number = MPI::process_number();
// Open mesh for editing
mesh.clear();
MeshEditor editor;
editor.open(mesh, tdim, gdim);
// Add vertices
editor.init_vertices(vertex_coordinates.size());
Point point(gdim);
dolfin_assert(vertex_indices.size() == vertex_coordinates.size());
for (std::size_t i = 0; i < vertex_coordinates.size(); ++i)
{
for (std::size_t j = 0; j < gdim; ++j)
point[j] = vertex_coordinates[i][j];
editor.add_vertex_global(i, vertex_indices[i], point);
}
// Add cells
editor.init_cells(cell_global_vertices.size());
const std::size_t num_cell_vertices = tdim + 1;
std::vector<std::size_t> cell(num_cell_vertices);
for (std::size_t i = 0; i < cell_global_vertices.size(); ++i)
{
for (std::size_t j = 0; j < num_cell_vertices; ++j)
{
// Get local cell vertex
std::map<std::size_t, std::size_t>::const_iterator iter
= vertex_global_to_local.find(cell_global_vertices[i][j]);
dolfin_assert(iter != vertex_global_to_local.end());
cell[j] = iter->second;
}
editor.add_cell(i, global_cell_indices[i], cell);
}
// Close mesh: Note that this must be done after creating the global
// vertex map or otherwise the ordering in mesh.close() will be wrong
// (based on local numbers).
editor.close();
// Set global number of cells and vertices
mesh.topology().init_global(0, num_global_vertices);
mesh.topology().init_global(tdim, num_global_cells);
// Construct boundary mesh
BoundaryMesh bmesh(mesh, "exterior");
const MeshFunction<std::size_t>& boundary_vertex_map = bmesh.entity_map(0);
const std::size_t boundary_size = boundary_vertex_map.size();
// Build sorted array of global boundary vertex indices (global
// numbering)
std::vector<std::size_t> global_vertex_send(boundary_size);
for (std::size_t i = 0; i < boundary_size; ++i)
global_vertex_send[i] = vertex_indices[boundary_vertex_map[i]];
std::sort(global_vertex_send.begin(), global_vertex_send.end());
// Receive buffer
std::vector<std::size_t> global_vertex_recv;
// Create shared_vertices data structure: mapping from shared vertices
// to list of neighboring processes
std::map<unsigned int, std::set<unsigned int> >& shared_vertices
= mesh.topology().shared_entities(0);
shared_vertices.clear();
// FIXME: Remove computation from inside communication loop
// Build shared vertex to sharing processes map
for (std::size_t i = 1; i < num_processes; ++i)
{
// We send data to process p - i (i steps to the left)
const int p = (process_number - i + num_processes) % num_processes;
// We receive data from process p + i (i steps to the right)
const int q = (process_number + i) % num_processes;
// Send and receive
MPI::send_recv(global_vertex_send, p, global_vertex_recv, q);
// Compute intersection of global indices
std::vector<std::size_t> intersection(std::min(global_vertex_send.size(),
global_vertex_recv.size()));
std::vector<std::size_t>::iterator intersection_end
= std::set_intersection(global_vertex_send.begin(),
global_vertex_send.end(),
global_vertex_recv.begin(),
global_vertex_recv.end(),
intersection.begin());
// Fill shared vertices information
std::vector<std::size_t>::const_iterator global_index;
for (global_index = intersection.begin(); global_index != intersection_end;
++global_index)
{
// Get local index
std::map<std::size_t, std::size_t>::const_iterator local_index;
local_index = vertex_global_to_local.find(*global_index);
dolfin_assert(local_index != vertex_global_to_local.end());
// Insert (local index, [proc])
shared_vertices[local_index->second].insert(q);
}
}
}
void save(output_archive& ar, const boost::multi_array<T, N,
Allocator>& marray, unsigned)
{
ar & make_array(marray.shape(), marray.num_dimensions());
ar & make_array(marray.data(), marray.num_elements());
}
//-----------------------------------------------------------------------------
void MeshPartitioning::distribute_cells(const LocalMeshData& mesh_data,
const std::vector<std::size_t>& cell_partition,
std::vector<std::size_t>& global_cell_indices,
boost::multi_array<std::size_t, 2>& cell_vertices)
{
// This function takes the partition computed by the partitioner
// (which tells us to which process each of the local cells stored in
// LocalMeshData on this process belongs. We use MPI::all_to_all to
// redistribute all cells (the global vertex indices of all cells).
// Number of MPI processes
const std::size_t num_processes = MPI::num_processes();
// Get dimensions of local mesh_data
const std::size_t num_local_cells = mesh_data.cell_vertices.size();
dolfin_assert(mesh_data.global_cell_indices.size() == num_local_cells);
const std::size_t num_cell_vertices = mesh_data.num_vertices_per_cell;
if (!mesh_data.cell_vertices.empty())
{
if (mesh_data.cell_vertices[0].size() != num_cell_vertices)
{
dolfin_error("MeshPartitioning.cpp",
"distribute cells",
"Mismatch in number of cell vertices (%d != %d) on process %d",
mesh_data.cell_vertices[0].size(), num_cell_vertices,
MPI::process_number());
}
}
// Build array of cell-vertex connectivity and partition vector
// Distribute the global cell number as well
std::vector<std::vector<std::size_t> > send_cell_vertices(num_processes);
for (std::size_t i = 0; i < num_local_cells; i++)
{
const std::size_t dest = cell_partition[i];
send_cell_vertices[dest].push_back(mesh_data.global_cell_indices[i]);
for (std::size_t j = 0; j < num_cell_vertices; j++)
send_cell_vertices[dest].push_back(mesh_data.cell_vertices[i][j]);
}
// Distribute cell-vertex connectivity
std::vector<std::vector<std::size_t> > received_cell_vertices(num_processes);
MPI::all_to_all(send_cell_vertices, received_cell_vertices);
// Count number of received cells
std::size_t num_new_local_cells = 0;
for (std::size_t p = 0; p < received_cell_vertices.size(); ++p)
{
num_new_local_cells
+= received_cell_vertices[p].size()/(num_cell_vertices + 1);
}
// Put mesh_data back into mesh_data.cell_vertices
cell_vertices.resize(boost::extents[num_new_local_cells][num_cell_vertices]);
global_cell_indices.resize(num_new_local_cells);
// Loop over new cells
std::size_t c = 0;
for (std::size_t p = 0; p < num_processes; ++p)
{
for (std::size_t i = 0; i < received_cell_vertices[p].size();
i += (num_cell_vertices + 1))
{
global_cell_indices[c] = received_cell_vertices[p][i];
for (std::size_t j = 0; j < num_cell_vertices; ++j)
cell_vertices[c][j] = received_cell_vertices[p][i + 1 + j];
++c;
}
}
}
//-----------------------------------------------------------------------------
void MeshPartitioning::distribute_vertices(const LocalMeshData& mesh_data,
const boost::multi_array<std::size_t, 2>& cell_vertices,
std::vector<std::size_t>& vertex_indices,
std::map<std::size_t, std::size_t>& vertex_global_to_local,
boost::multi_array<double, 2>& vertex_coordinates)
{
// This function distributes all vertices (coordinates and
// local-to-global mapping) according to the cells that are stored on
// each process. This happens in several stages: First each process
// figures out which vertices it needs (by looking at its cells)
// and where those vertices are located. That information is then
// distributed so that each process learns where it needs to send
// its vertices.
// Get number of processes
const std::size_t num_processes = MPI::num_processes();
// Get geometric dimension
const std::size_t gdim = mesh_data.gdim;
// Compute which vertices we need
std::set<std::size_t> needed_vertex_indices;
boost::multi_array<std::size_t, 2>::const_iterator vertices;
for (vertices = cell_vertices.begin(); vertices != cell_vertices.end();
++vertices)
{
needed_vertex_indices.insert(vertices->begin(), vertices->end());
}
// Compute where (process number) the vertices we need are located
std::vector<std::vector<std::size_t> > send_vertex_indices(num_processes);
std::vector<std::vector<std::size_t> > vertex_location(num_processes);
std::set<std::size_t>::const_iterator required_vertex;
for (required_vertex = needed_vertex_indices.begin();
required_vertex != needed_vertex_indices.end(); ++required_vertex)
{
// Get process that has required vertex
const std::size_t location
= MPI::index_owner(*required_vertex, mesh_data.num_global_vertices);
send_vertex_indices[location].push_back(*required_vertex);
vertex_location[location].push_back(*required_vertex);
}
// Send required vertices to other processes, and receive back vertices
// required by other processes.
std::vector<std::vector<std::size_t> > received_vertex_indices;
MPI::all_to_all(send_vertex_indices, received_vertex_indices);
// Distribute vertex coordinates
std::vector<std::vector<double> > send_vertex_coordinates(num_processes);
const std::pair<std::size_t, std::size_t> local_vertex_range
= MPI::local_range(mesh_data.num_global_vertices);
for (std::size_t p = 0; p < num_processes; ++p)
{
send_vertex_coordinates[p].reserve(received_vertex_indices[p].size()*gdim);
for (std::size_t i = 0; i < received_vertex_indices[p].size(); ++i)
{
dolfin_assert(received_vertex_indices[p][i] >= local_vertex_range.first
&& received_vertex_indices[p][i] < local_vertex_range.second);
const std::size_t location
= received_vertex_indices[p][i] - local_vertex_range.first;
for (std::size_t j = 0; j < gdim; ++j)
send_vertex_coordinates[p].push_back(mesh_data.vertex_coordinates[location][j]);
}
}
std::vector<std::vector<double> > received_vertex_coordinates;
MPI::all_to_all(send_vertex_coordinates, received_vertex_coordinates);
// Set index counters to first position in receive buffers
std::vector<std::size_t> index_counters(num_processes, 0);
// Clear data
vertex_indices.clear();
vertex_global_to_local.clear();
// Count number of local vertices
std::size_t num_local_vertices = 0;
for (std::size_t p = 0; p < num_processes; ++p)
num_local_vertices += received_vertex_coordinates[p].size()/gdim;
// Store coordinates and construct global to local mapping
vertex_coordinates.resize(boost::extents[num_local_vertices][gdim]);
vertex_indices.resize(num_local_vertices);
std::size_t v = 0;
for (std::size_t p = 0; p < num_processes; ++p)
{
for (std::size_t i = 0; i < received_vertex_coordinates[p].size();
i += gdim)
{
for (std::size_t j = 0; j < gdim; ++j)
vertex_coordinates[v][j] = received_vertex_coordinates[p][i + j];
const std::size_t global_vertex_index
= vertex_location[p][index_counters[p]++];
vertex_global_to_local[global_vertex_index] = v;
vertex_indices[v] = global_vertex_index;
++v;
}
}
}
std::int32_t GraphBuilder::compute_local_dual_graph_keyed(
const MPI_Comm mpi_comm,
const boost::multi_array<std::int64_t, 2>& cell_vertices,
const CellType& cell_type,
std::vector<std::vector<std::size_t>>& local_graph,
FacetCellMap& facet_cell_map)
{
Timer timer("Compute local part of mesh dual graph");
const std::int8_t tdim = cell_type.dim();
const std::int32_t num_local_cells = cell_vertices.shape()[0];
const std::int8_t num_vertices_per_cell = cell_type.num_entities(0);
const std::int8_t num_facets_per_cell = cell_type.num_entities(tdim - 1);
const std::int8_t num_vertices_per_facet = cell_type.num_vertices(tdim - 1);
dolfin_assert(N == num_vertices_per_facet);
dolfin_assert(num_local_cells == (int) cell_vertices.shape()[0]);
dolfin_assert(num_vertices_per_cell == (int) cell_vertices.shape()[1]);
local_graph.resize(num_local_cells);
facet_cell_map.clear();
// Compute local edges (cell-cell connections) using global
// (internal to this function, not the user numbering) numbering
// Get offset for this process
const std::int64_t cell_offset = MPI::global_offset(mpi_comm, num_local_cells,
true);
// Create map from cell vertices to entity vertices
boost::multi_array<unsigned int, 2>
facet_vertices(boost::extents[num_facets_per_cell][num_vertices_per_facet]);
std::vector<unsigned int> v(num_vertices_per_cell);
std::iota(v.begin(), v.end(), 0);
cell_type.create_entities(facet_vertices, tdim - 1, v.data());
// Vector-of-arrays data structure, which is considerably faster than
// vector-of-vectors.
std::vector<std::pair<std::array<std::int32_t, N>, std::int32_t>>
facets(num_facets_per_cell*num_local_cells);
// Iterate over all cells and build list of all facets (keyed on
// sorted vertex indices), with cell index attached
int counter = 0;
for (std::int32_t i = 0; i < num_local_cells; ++i)
{
// Iterate over facets of cell
for (std::int8_t j = 0; j < num_facets_per_cell; ++j)
{
// Get list of facet vertices
auto& facet = facets[counter].first;
for (std::int8_t k = 0; k < N; ++k)
facet[k] = cell_vertices[i][facet_vertices[j][k]];
// Sort facet vertices
std::sort(facet.begin(), facet.end());
// Attach local cell index
facets[counter].second = i;
// Increment facet counter
counter++;
}
}
// Sort facets
std::sort(facets.begin(), facets.end());
// Find maching facets by comparing facet i and facet i -1
std::size_t num_local_edges = 0;
for (std::size_t i = 1; i < facets.size(); ++i)
{
const int ii = i;
const int jj = i - 1;
const auto& facet0 = facets[jj].first;
const auto& facet1 = facets[ii].first;
const int cell_index0 = facets[jj].second;
if (std::equal(facet1.begin(), facet1.end(), facet0.begin()))
{
// Add edges (directed graph, so add both ways)
const int cell_index1 = facets[ii].second;
local_graph[cell_index0].push_back(cell_index1 + cell_offset);
local_graph[cell_index1].push_back(cell_index0 + cell_offset);
// Since we've just found a matching pair, the next pair cannot be
// matching, so advance 1
++i;
// Increment number of local edges found
++num_local_edges;
}
else
{
// No match, so add facet0 to map
//facet_cell_map.insert(facet_cell_map.end(), {std::vector<std::size_t>(facet0.begin(),
// facet0.end()), cell_index0});
facet_cell_map.push_back({std::vector<std::size_t>(facet0.begin(),
facet0.end()), cell_index0});
}
}
// Add last facet, as it's not covered by the above loop. We could
// check it against the preceding facet, but it's easier to just
// insert it here
if (!facets.empty())
{
const int k = facets.size() - 1;
const int cell_index = facets[k].second;
facet_cell_map.push_back({std::vector<std::size_t>(facets[k].first.begin(),
facets[k].first.end()), cell_index});
}
return num_local_edges;
}
//-----------------------------------------------------------------------------
std::int32_t GraphBuilder::compute_nonlocal_dual_graph(
const MPI_Comm mpi_comm,
const boost::multi_array<std::int64_t, 2>& cell_vertices,
const CellType& cell_type,
const std::int64_t num_global_vertices,
std::vector<std::vector<std::size_t>>& local_graph,
FacetCellMap& facet_cell_map,
std::set<std::int64_t>& ghost_vertices)
{
log(PROGRESS, "Build nonlocal part of mesh dual graph");
Timer timer("Compute non-local part of mesh dual graph");
// Get number of MPI processes, and return if mesh is not distributed
const int num_processes = MPI::size(mpi_comm);
if (num_processes == 1)
return 0;
// At this stage facet_cell map only contains facets->cells with
// edge facets either interprocess or external boundaries
const int tdim = cell_type.dim();
// List of cell vertices
const std::int32_t num_local_cells = cell_vertices.shape()[0];
const std::int8_t num_vertices_per_cell = cell_type.num_entities(0);
const std::int8_t num_vertices_per_facet = cell_type.num_vertices(tdim - 1);
dolfin_assert(num_local_cells == (int) cell_vertices.shape()[0]);
dolfin_assert(num_vertices_per_cell == (int) cell_vertices.shape()[1]);
// Compute local edges (cell-cell connections) using global
// (internal to this function, not the user numbering) numbering
// Get offset for this process
const std::int64_t offset = MPI::global_offset(mpi_comm, num_local_cells,
true);
// Send facet-cell map to intermediary match-making processes
std::vector<std::vector<std::size_t>> send_buffer(num_processes);
std::vector<std::vector<std::size_t>> received_buffer(num_processes);
// Pack map data and send to match-maker process
for (auto &it : facet_cell_map)
{
// FIXME: Could use a better index? First vertex is slightly
// skewed towards low values - may not be important
// Use first vertex of facet to partition into blocks
const int dest_proc = MPI::index_owner(mpi_comm, (it.first)[0],
num_global_vertices);
// Pack map into vectors to send
send_buffer[dest_proc].insert(send_buffer[dest_proc].end(),
it.first.begin(), it.first.end());
// Add offset to cell numbers sent off process
send_buffer[dest_proc].push_back(it.second + offset);
}
// FIXME: This does not look memory scalable. Switch to 'post-office' model.
// Send data
MPI::all_to_all(mpi_comm, send_buffer, received_buffer);
// Clear send buffer
send_buffer = std::vector<std::vector<std::size_t>>(num_processes);
// Map to connect processes and cells, using facet as key
typedef boost::unordered_map<std::vector<std::size_t>,
std::pair<std::size_t, std::size_t>> MatchMap;
MatchMap matchmap;
// Look for matches to send back to other processes
std::pair<std::vector<std::size_t>,
std::pair<std::size_t, std::size_t>> key;
key.first.resize(num_vertices_per_facet);
for (int p = 0; p < num_processes; ++p)
{
// Unpack into map
const std::vector<std::size_t>& data_p = received_buffer[p];
for (auto it = data_p.begin(); it != data_p.end();
it += (num_vertices_per_facet + 1))
{
// Build map key
std::copy(it, it + num_vertices_per_facet, key.first.begin());
key.second.first = p;
key.second.second = *(it + num_vertices_per_facet);
// Perform map insertion/look-up
std::pair<MatchMap::iterator, bool> data = matchmap.insert(key);
// If data is already in the map, extract data and remove from
// map
if (!data.second)
{
// Found a match of two facets - send back to owners
const std::size_t proc1 = data.first->second.first;
const std::size_t proc2 = p;
const std::size_t cell1 = data.first->second.second;
const std::size_t cell2 = key.second.second;
send_buffer[proc1].push_back(cell1);
send_buffer[proc1].push_back(cell2);
send_buffer[proc2].push_back(cell2);
send_buffer[proc2].push_back(cell1);
// Remove facet - saves memory and search time
matchmap.erase(data.first);
}
}
}
// Send matches to other processes
MPI::all_to_all(mpi_comm, send_buffer, received_buffer);
// Clear ghost vertices
ghost_vertices.clear();
// Flatten received data and insert connected cells into local map
std::int32_t num_nonlocal_edges = 0;
for (std::size_t p = 0; p < received_buffer.size(); ++p)
{
const std::vector<std::size_t>& cell_list = received_buffer[p];
for (std::size_t i = 0; i < cell_list.size(); i += 2)
{
dolfin_assert((std::int64_t) cell_list[i] >= offset);
dolfin_assert((std::int64_t) (cell_list[i] - offset)
< (std::int64_t) local_graph.size());
//local_graph[cell_list[i] - offset].insert(cell_list[i + 1]);
auto& edges = local_graph[cell_list[i] - offset];
auto it = std::find(edges.begin(), edges.end(), cell_list[i + 1]);
if (it == local_graph[cell_list[i] - offset].end())
edges.push_back(cell_list[i + 1]);
ghost_vertices.insert(cell_list[i + 1]);
}
++num_nonlocal_edges;
}
return num_nonlocal_edges;
}
/** \brief get the centroid of the neighbourhood of an image pixel given by it's offset */
valarray<double> centroid::operator()(const size_t& l) const
{
const int scope = 1;
//convert the raveled index to 3D indices
size_t
i = l / image.strides()[0],
j = (l % image.strides()[0]) / image.strides()[1],
k = (l % image.strides()[0]) % image.strides()[1];
//cout<<"l="<<l<<" -> i="<<i<<" j="<<j<<" k="<<k<<" ... ";
//the data of the neighbourhood view are copied together for the coder's sanity
boost::multi_array<float,3> ngb =
image[boost::indices
[image.shape()[0]<2*scope+1 ? range() : range(i-scope, i+scope+1)]
[image.shape()[1]<2*scope+1 ? range() : range(j-scope, j+scope+1)]
[image.shape()[2]<2*scope+1 ? range() : range(k-scope, k+scope+1)]
];
//Find the extrema of the neighbourhood.
std::pair<float*, float*> minmax = boost::minmax_element(ngb.origin(), ngb.origin()+ngb.num_elements());
//If the neighbourhood contains a negative pixel, we are at the edge of a Fourier filtering artefact that should not be considered a particle
if(*minmax.first < 0)
return valarray<double>(-1.0, 3);
//marking non local maxima (including diagonals)
if(image.origin()[l] != *minmax.second)
return valarray<double>(-1.0, 3);
//calculation of the intensity centroid
valarray<double> c(0.0,3);
double total_w = 0.0;
float *px = ngb.origin();
for(int x=0; x<ngb.shape()[0];++x)
for(int y=0; y<ngb.shape()[1];++y)
for(int z=0; z<ngb.shape()[2];++z)
{
const double weight = pow((double)(x-scope), 2) + pow((double)(y-scope), 2) + pow((double)(z-scope), 2) * (double)(*px);
c[0] += (x-scope)*weight;
c[1] += (y-scope)*weight;
c[2] += (z-scope)*weight;
total_w += weight ;
px++;
}
//cout<<c[0]<<"\t"<<c[1]<<"\t"<<c[2]<<endl;
//cout<<"divide by a weight of "<<total_w<<endl;
c /= total_w/pow(2.0*scope+1, 2);
//cout<<c[0]<<"\t"<<c[1]<<"\t"<<c[2]<<endl;
//c /= (double)accumulate(ngb.origin(), ngb.origin()+ngb.num_elements(), 0.0);
//double sum = accumulate(ngb.origin(),ngb.origin()+ngb.num_elements(),0.0);
//cout<<"valarrays ... ";
/*valarray<double> c(0.0,3), pos(0.0,3), middle(0.0,3);
for(size_t d=0; d<3;++d)
middle[d] = ngb.shape()[d]/3;
float *v = ngb.origin();
for(pos[0]=0;pos[0]<ngb.shape()[0];++pos[0])
for(pos[1]=0;pos[1]<ngb.shape()[1];++pos[1])
for(pos[2]=0;pos[2]<ngb.shape()[2];++pos[2])
c += (pos-middle) * (*v++);//pow(*v++, 2.0f);
c /= image.origin()[l];//pow(image.origin()[l], 2.0f);
for(size_t d=0;d<3;++d)
c[d] = (c[d]<0?-1:1) * sqrt(abs(c[d]))/4.5;*/
c[0] += i;
c[1] += j;
c[2] += k;
return c;
};
boost::multi_array<double, DIMENSION>
get_imag_parts(const boost::multi_array<SCALAR, DIMENSION> &data) {
boost::multi_array<double, DIMENSION> imag_part(data.shape());
std::transform(data.begin(), data.end(), imag_part.begin(), get_imag);
return imag_part;
}
void Octtree::find_cell_ranks( const boost::multi_array<Real,2>& coordinates, std::vector<Uint>& ranks )
{
ranks.resize(coordinates.size());
Handle< Elements > element_component;
Uint element_idx;
std::deque<Uint> missing_cells;
RealVector dummy(m_dim);
for(Uint i=0; i<coordinates.size(); ++i)
{
for (Uint d=0; d<m_dim; ++d)
dummy[d] = coordinates[i][d];
if( find_element(dummy,element_component,element_idx) )
{
ranks[i] = Comm::instance().rank();
}
else
{
ranks[i] = math::Consts::uint_max();
missing_cells.push_back(i);
}
}
std::vector<Real> send_coords(m_dim*missing_cells.size());
std::vector<Real> recv_coords;
Uint c(0);
boost_foreach(const Uint i, missing_cells)
{
for(Uint d=0; d<m_dim; ++d)
send_coords[c++]=coordinates[i][d];
}
for (Uint root=0; root<PE::Comm::instance().size(); ++root)
{
recv_coords.resize(0);
PE::Comm::instance().broadcast(send_coords,recv_coords,root,m_dim);
// size is only because it doesn't get resized for this rank
std::vector<Uint> send_found(missing_cells.size(),math::Consts::uint_max());
if (root!=Comm::instance().rank())
{
std::vector<RealVector> recv_coordinates(recv_coords.size()/m_dim) ;
boost_foreach(RealVector& realvec, recv_coordinates)
realvec.resize(m_dim);
c=0;
for (Uint i=0; i<recv_coordinates.size(); ++i)
{
for(Uint d=0; d<m_dim; ++d)
recv_coordinates[i][d]=recv_coords[c++];
}
send_found.resize(recv_coordinates.size());
for (Uint i=0; i<recv_coordinates.size(); ++i)
{
if( find_element(recv_coordinates[i],element_component,element_idx) )
{
send_found[i] = Comm::instance().rank();
}
else
send_found[i] = math::Consts::uint_max();
}
}
std::vector<Uint> recv_found(missing_cells.size()*Comm::instance().size());
PE::Comm::instance().gather(send_found,recv_found,root);
if( root==Comm::instance().rank())
{
const Uint stride = missing_cells.size();
for (Uint i=0; i<missing_cells.size(); ++i)
{
for(Uint p=0; p<Comm::instance().size(); ++p)
{
ranks[missing_cells[i]] = std::min(recv_found[i+p*stride] , ranks[missing_cells[i]]);
}
}
}
}
}
size_t cols(const boost::multi_array<T, N>& arr)
{
return arr.shape()[1];
}
size_t rows(const boost::multi_array<T, N>& arr)
{
return arr.shape()[0];
}
/** Returns the total number of elements in the buffer
Equal to get_range()[0] * ... * get_range()[dimensions-1].
*/
auto get_count() const {
return allocation.num_elements();
}
// writes a 2d array containing rgb information into a png file
bool write_png(const boost::multi_array<png::rgb,2>& pixel,
const char* filename)
{
FILE *fp=NULL;
fp = fopen(filename, "wb");
if(fp==NULL) {
printf("write_png: error writing file %s\n", filename);
return false;
}
// we need to copy the data into an array
png_byte **Array;
int height, width;
height=pixel.shape()[0];
width=pixel.shape()[1];
Array = new png_byte*[height];
for(int i=0; i<height; i++) {
Array[i] = new png_byte[3*width];
for(int j=0; j<width; j++) {
assert( pixel[i][j].r<=255 );
assert( pixel[i][j].g<=255 );
assert( pixel[i][j].b<=255 );
Array[i][3*j]=(png_byte) pixel[i][j].r;
Array[i][3*j+1]=(png_byte) pixel[i][j].g;
Array[i][3*j+2]=(png_byte) pixel[i][j].b;
}
}
// initialise png_struct and png_info
png_structp png_ptr;
png_infop info_ptr;
png_ptr = png_create_write_struct(PNG_LIBPNG_VER_STRING,
NULL,writepng_error_handler,NULL);
if(!png_ptr) {
printf("write_png: error initialising png_ptr\n");
return(false);
}
info_ptr = png_create_info_struct(png_ptr);
if(!info_ptr) {
printf("write_png: error creating info_ptr\n");
png_destroy_write_struct(&png_ptr, (png_infopp)NULL);
return(false);
}
// set error handling (very strange!)
if(setjmp(png_jmpbuf(png_ptr))) {
printf("write_png: general error\n");
png_destroy_write_struct(&png_ptr, &info_ptr);
fclose(fp);
return(false);
}
// making sure fp is opened in binary mode
png_init_io(png_ptr, fp);
// set image parameters
png_set_compression_level(png_ptr, Z_BEST_COMPRESSION);
png_set_IHDR(png_ptr, info_ptr, width, height,
8, PNG_COLOR_TYPE_RGB, PNG_INTERLACE_NONE,
PNG_COMPRESSION_TYPE_DEFAULT, PNG_FILTER_TYPE_DEFAULT);
// writing the header
png_write_info(png_ptr, info_ptr);
// writing the actual data, provided by pointers to rows
png_write_image(png_ptr, Array);
// finishing up
png_write_end(png_ptr, info_ptr);
png_destroy_write_struct(&png_ptr, &info_ptr);
for(int i=0; i<height; i++) {
delete[] Array[i];
}
delete[] Array;
fclose(fp);
return true;
}