void mouse_callback( int button, int state, int x, int y ){
if( state == 0 ){
for( int i = 0; i < nodes_len; i++ ){
if( return_dist_sqr( x, y, nodes[i].x, nodes[i].y ) <= nodes[i].radius*nodes[i].radius ){
if( button_press_count == 0 ){
nodes[i].is_start = true;
button_press_count += 1;
start = nodes[i];
}else if( button_press_count == 1 ){
nodes[i].is_end = true;
button_press_count += 1;
end = nodes[i];
shortest_path( nodes, nodes_len, start, end );
}else if( button_press_count == 2 ){
button_press_count = 0;
for( int x = 0; x < nodes_len; x++ ){
nodes[x].is_end = false;
nodes[x].is_start = false;
}
}
}
}
}
}
///////////////////////////////////////////////////////////////////////////////////////////////////////////
// input
void mouse_motion_callback( int x, int y ){
for( int i = 0; i < nodes_len; i++ ){
if( return_dist_sqr( x, y, nodes[i].x, nodes[i].y ) <= nodes[i].radius*nodes[i].radius ){
nodes[i].hover = true;
}else{
nodes[i].hover = false;
}
}
}
// cycle through array of nodes to add links to the ones within the given range
void create_links( Node * n, int n_len, float range ){
for( int i = 0; i < n_len; i++ ){
for( int x = i; x < n_len; x++ ){
if( x != i && return_dist_sqr( n[i].x, n[i].y, n[x].x, n[x].y ) < range*range ){
//std::cout << "coonnect \n";
n[i].add_link( &n[x], true );
n[x].add_link( &n[i], false );
}
}
}
}
void
KDTree::neighborSearch(Point & query_point,
unsigned int patch_size,
std::vector<std::size_t> & return_index)
{
// The query point has to be converted from a C++ array to a C array because nanoflann library
// expects C arrays.
const Real query_pt[] = {query_point(0), query_point(1), query_point(2)};
return_index.resize(patch_size, std::numeric_limits<std::size_t>::max());
std::vector<Real> return_dist_sqr(patch_size, std::numeric_limits<Real>::max());
_kd_tree->knnSearch(&query_pt[0], patch_size, &return_index[0], &return_dist_sqr[0]);
if (return_dist_sqr[0] == std::numeric_limits<Real>::max() ||
return_index[0] == std::numeric_limits<std::size_t>::max())
mooseError("Unable to find closest node!");
}
