void SSfind::prep_xmap( const clipper::Xmap<float>& xmap, const double radius )
{
// make a 1-d array of gridded density values covering ASU+border
grid = xmap.grid_sampling();
grrot = xmap.operator_orth_grid().rot();
clipper::Grid_range gr0 = xmap.grid_asu();
clipper::Grid_range gr1( xmap.cell(), xmap.grid_sampling(), radius );
mxgr = clipper::Grid_range( gr0.min()+gr1.min(), gr0.max()+gr1.max() );
mapbox = std::vector<float>( mxgr.size(), 0.0 );
// make 1d list of densities
clipper::Xmap<float>::Map_reference_index ix( xmap );
for ( int i = 0; i < mapbox.size(); i++ ) {
ix.set_coord( mxgr.deindex( i ) );
mapbox[i] = xmap[ix];
}
}
void SSfind::prep_search( const clipper::Xmap<float>& xmap, const double rhocut, const double radcut, const clipper::Coord_orth centre )
{
// make list of results
typedef clipper::Xmap<float>::Map_reference_index MRI;
srctrn.clear();
double r2cut = ( radcut > 0.0 ) ? radcut*radcut : 1.0e20;
clipper::Coord_frac cf = centre.coord_frac( xmap.cell() );
for ( MRI ix = xmap.first(); !ix.last(); ix.next() )
if ( xmap[ix] > rhocut ) {
clipper::Coord_frac df = ix.coord().coord_frac( xmap.grid_sampling() );
df = df.symmetry_copy_near( xmap.spacegroup(), xmap.cell(), cf ) - cf;
double r2 = df.lengthsq( xmap.cell() );
if ( r2 < r2cut )
srctrn.push_back( grid.index( ix.coord() ) );
}
}
/*! A log-likelihood FFFear search is performed for the target in the given map.
\param resultscr The best scores.
\param resultrot The best rotations.
\param resulttrn The best translations.
\param xmap The map to search.
\param rtops The oprientations to search. */
void LLK_map_target::search( clipper::Xmap<float>& resultscr, clipper::Xmap<int>& resultrot, clipper::Xmap<int>& resulttrn, const clipper::Xmap<float>& xmap, const std::vector<clipper::RTop_orth>& rtops ) const
{
// set up results
const clipper::Spacegroup& spgr = xmap.spacegroup();
const clipper::Cell& cell = xmap.cell();
const clipper::Grid_sampling& grid = xmap.grid_sampling();
resultscr.init( spgr, cell, grid );
resultrot.init( spgr, cell, grid );
resulttrn.init( spgr, cell, grid );
resultscr = 1.0e20;
// now search for ML target in each orientation in turn
clipper::Xmap<float> resultp1( clipper::Spacegroup::p1(), cell, grid );
clipper::Xmap<float>::Map_reference_index i1(resultp1);
clipper::Xmap<float>::Map_reference_coord ix(resultscr);
// set up z scoring
clipper::FFFear_fft<float> srch( xmap );
clipper::NX_operator nxop( xmap, target, rtops[0] );
srch( resultp1, target, weight, nxop );
clipper::Map_stats zstats( resultp1 );
// loop over orientations
for ( int op = 0; op < rtops.size(); op++ ) {
// do the fffear search
clipper::NX_operator nxop( xmap, target, rtops[op].inverse() );
srch( resultp1, target, weight, nxop );
// store best scores
for ( i1 = resultp1.first(); !i1.last(); i1.next() ) {
ix.set_coord( i1.coord() );
float score = ( resultp1[i1] - zstats.mean() ) / zstats.std_dev();
if ( score < resultscr[ix] ) {
resultscr[ix] = score;
resultrot[ix] = op;
resulttrn[ix] = grid.index( i1.coord() );
}
}
}
}
