/** @brief Drag finger on screen, now release your finger.
* @param p [in] Point where we release the finger.
* @return true when correct.
*/
bool ChandWriter::onPaintingStop( const Cpoint &point)
{
if ( m_surface ==NULL)
{
return false;
}
//p =CdialogEvent::Instance()->lastMouse();
Cpoint p =point-(m_rect.leftTop()*8);
addPoint( p.x, p.y);
//zinnia_character_add( m_character, m_stroke, p.x, p.y);
#ifdef USE_SDL2
m_graphics->setRenderArea( m_surface);
m_graphics->line( m_lastPoint.x, m_lastPoint.y, p.x, p.y);
m_graphics->setRenderArea( NULL);
#else
CtextSurface::line( m_surface, m_lastPoint, p);
#endif
m_started =false;
m_stroke++;
m_lastPoint =Cpoint(-100,-100);
#ifdef USE_ZINNIA
if ( Cgraphics::m_defaults.handwriting_detection_enabled)
{
if ( m_result)
{
zinnia_result_destroy( m_result);
m_result =NULL;
}
m_result = zinnia_recognizer_classify( m_recognizer, m_character, 50);
}
#endif
return true;
}
/** @brief Clear the handwriter background. */
void ChandWriter::clearImage()
{
if ( Cgraphics::m_defaults.handwriting_detection_enabled)
{
#ifdef USE_SDL2
assert(0);
#else
SDL_Rect rect;
rect.h =(Uint16)m_surface->h;
rect.w =(Uint16)m_surface->w;
rect.x =0;
rect.y =0;
SDL_FillRect( m_surface, &rect, m_background.getColour());
#endif
m_stroke =0;
m_index =0;
m_lastPoint =Cpoint(-5,-100);
#ifdef USE_ZINNIA
if ( m_character)
{
zinnia_character_clear( m_character);
zinnia_character_set_width( m_character, m_rect.width()*8);
zinnia_character_set_height( m_character, m_rect.height()*8);
}
#endif
}
}
unsigned short int Cline::intersectionsWithCircle(Cpoint c, double r, vector<Cpoint> &intersections)
{
intersections.clear();
// move circle to (0,0)
//Cpoint p1 = aa - c; cout << "DEBUG: p1 is " << p1 << endl;
//Cpoint p2 = bb - c; cout << "DEBUG: p2 is " << p2 << endl;
Cpoint p1(aa.get_xx() - c.get_xx(), aa.get_yy() - c.get_yy()); //cout << "DEBUG: p1 is " << p1 << endl;
Cpoint p2(bb.get_xx() - c.get_xx(), bb.get_yy() - c.get_yy()); //cout << "DEBUG: p1 is " << p1 << endl;
// discriminant
double dx = p2.get_xx() - p1.get_xx();
double dy = p2.get_yy() - p1.get_yy();
double dr_sq = dx*dx + dy*dy;
double D = p1.get_xx() * p2.get_yy() - p2.get_xx() * p1.get_yy();
double disc = r*r * dr_sq - D*D;
if(disc < 0)
return 0;
else if(disc == 0)
{
double x = D * dy / dr_sq;
double y = -D * dx / dr_sq;
// check if point belongs to segment
Cpoint i = Cpoint(x + c.get_xx(), y + c.get_yy());
if( i.d2point2(&aa) <= aa.d2point2(&bb) && i.d2point2(&bb) <= aa.d2point2(&bb))
intersections.push_back( i );
return intersections.size();
}
else
{
int sign_dy = (dy >= 0) ? 1 : -1;
double x1 = ( D * dy + sign_dy * dx * sqrt(disc) ) / dr_sq;
double x2 = ( D * dy - sign_dy * dx * sqrt(disc) ) / dr_sq;
double abs_dy = ( dy >= 0 ) ? dy : -dy;
double y1 = ( -D * dx + abs_dy * sqrt(disc) ) / dr_sq;
double y2 = ( -D * dx - abs_dy * sqrt(disc) ) / dr_sq;
Cpoint i1 = Cpoint(x1 + c.get_xx(), y1 + c.get_yy());
Cpoint i2 = Cpoint(x2 + c.get_xx(), y2 + c.get_yy());
if( i1.d2point2(&aa) <= aa.d2point2(&bb) && i1.d2point2(&bb) <= aa.d2point2(&bb))
intersections.push_back( i1 );
if( i2.d2point2(&aa) <= aa.d2point2(&bb) && i2.d2point2(&bb) <= aa.d2point2(&bb))
intersections.push_back( i2 );
return intersections.size();
}
}
// -----------------------------------------------------------------------------
int Cluster_DPeaks::Cluster_DiscreteDensity() {
mprintf("\tStarting DPeaks clustering, discrete density calculation.\n");
Points_.clear();
// First determine which frames are being clustered.
for (int frame = 0; frame < (int)FrameDistances_.Nframes(); ++frame)
if (!FrameDistances_.IgnoringRow( frame ))
Points_.push_back( Cpoint(frame) );
// Sanity check.
if (Points_.size() < 2) {
mprinterr("Error: Only 1 frame in initial clustering.\n");
return 1;
}
// For each point, determine how many others are within epsilon. Also
// determine maximum distance between any two points.
mprintf("\tDetermining local density of each point.\n");
ProgressBar cluster_progress( Points_.size() );
double maxDist = -1.0;
for (Carray::iterator point0 = Points_.begin();
point0 != Points_.end(); ++point0)
{
cluster_progress.Update(point0 - Points_.begin());
int density = 0;
for (Carray::const_iterator point1 = Points_.begin();
point1 != Points_.end(); ++point1)
{
if (point0 != point1) {
double dist = FrameDistances_.GetFdist(point0->Fnum(), point1->Fnum());
maxDist = std::max(maxDist, dist);
if ( dist < epsilon_ )
density++;
}
}
point0->SetPointsWithinEps( density );
}
mprintf("DBG: Max dist= %g\n", maxDist);
// DEBUG: Frame/Density
CpptrajFile fdout;
fdout.OpenWrite("fd.dat");
for (Carray::const_iterator point = Points_.begin(); point != Points_.end(); ++point)
fdout.Printf("%i %i\n", point->Fnum()+1, point->PointsWithinEps());
fdout.CloseFile();
// Sort by density here. Otherwise array indices will be invalid later.
std::sort( Points_.begin(), Points_.end(), Cpoint::pointsWithinEps_sort() );
// For each point, find the closest point that has higher density. Since
// array is now sorted by density the last point has the highest density.
Points_.back().SetDist( maxDist );
mprintf("\tFinding closest neighbor point with higher density for each point.\n");
unsigned int lastidx = Points_.size() - 1;
cluster_progress.SetupProgress( lastidx );
for (unsigned int idx0 = 0; idx0 != lastidx; idx0++)
{
cluster_progress.Update( idx0 );
double min_dist = maxDist;
int nearestIdx = -1; // Index of nearest neighbor with higher density
Cpoint& point0 = Points_[idx0];
//mprintf("\nDBG:\tSearching for nearest neighbor to idx %u with higher density than %i.\n",
// idx0, point0.PointsWithinEps());
// Since array is sorted by density we can start at the next point.
for (unsigned int idx1 = idx0+1; idx1 != Points_.size(); idx1++)
{
Cpoint const& point1 = Points_[idx1];
double dist1_2 = FrameDistances_.GetFdist(point0.Fnum(), point1.Fnum());
if (point1.PointsWithinEps() > point0.PointsWithinEps())
{
if (dist1_2 < min_dist) {
min_dist = dist1_2;
nearestIdx = (int)idx1;
//mprintf("DBG:\t\tNeighbor idx %i is closer (density %i, distance %g)\n",
// nearestIdx, point1.PointsWithinEps(), min_dist);
}
}
}
point0.SetDist( min_dist );
//mprintf("DBG:\tClosest point to %u with higher density is %i (distance %g)\n",
// idx0, nearestIdx, min_dist);
point0.SetNearestIdx( nearestIdx );
}
// Plot density vs distance for each point.
if (!dvdfile_.empty()) {
CpptrajFile output;
if (output.OpenWrite(dvdfile_))
mprinterr("Error: Could not open density vs distance plot '%s' for write.\n",
dvdfile_.c_str()); // TODO: Make fatal?
else {
output.Printf("%-10s %10s %s %10s %10s\n", "#Density", "Distance",
"Frame", "Idx", "Neighbor");
for (Carray::const_iterator point = Points_.begin();
point != Points_.end(); ++point)
output.Printf("%-10i %10g \"%i\" %10u %10i\n", point->PointsWithinEps(), point->Dist(),
point->Fnum()+1, point-Points_.begin(), point->NearestIdx());
output.CloseFile();
}
}
return 0;
}
// -----------------------------------------------------------------------------
int Cluster_DPeaks::Cluster_GaussianKernel() {
mprintf("\tStarting DPeaks clustering. Using Gaussian kernel to calculate density.\n");
// First determine which frames are being clustered.
Points_.clear();
int oidx = 0;
for (int frame = 0; frame < (int)FrameDistances_.Nframes(); ++frame)
if (!FrameDistances_.IgnoringRow( frame ))
Points_.push_back( Cpoint(frame, oidx++) );
// Sanity check.
if (Points_.size() < 2) {
mprinterr("Error: Only 1 frame in initial clustering.\n");
return 1;
}
// Sort distances
std::vector<float> Distances;
for (ClusterMatrix::const_iterator mat = FrameDistances_.begin();
mat != FrameDistances_.end(); ++mat)
Distances.push_back( *mat );
std::sort( Distances.begin(), Distances.end() );
unsigned int idx = (unsigned int)((double)Distances.size() * 0.02);
double bandwidth = (double)Distances[idx];
mprintf("idx= %u, bandwidth= %g\n", idx, bandwidth);
// Density via Gaussian kernel
double maxDist = -1.0;
for (unsigned int i = 0; i != Points_.size(); i++) {
for (unsigned int j = i+1; j != Points_.size(); j++) {
double dist = FrameDistances_.GetFdist(Points_[i].Fnum(), Points_[j].Fnum());
maxDist = std::max( maxDist, dist );
dist /= bandwidth;
double gk = exp(-(dist *dist));
Points_[i].AddDensity( gk );
Points_[j].AddDensity( gk );
}
}
mprintf("Max dist= %g\n", maxDist);
CpptrajFile rhoOut;
rhoOut.OpenWrite("rho.dat");
for (unsigned int i = 0; i != Points_.size(); i++)
rhoOut.Printf("%u %g\n", i+1, Points_[i].Density());
rhoOut.CloseFile();
// Sort by density, descending
std::stable_sort( Points_.begin(), Points_.end(), Cpoint::density_sort_descend() );
CpptrajFile ordrhoOut;
ordrhoOut.OpenWrite("ordrho.dat");
for (unsigned int i = 0; i != Points_.size(); i++)
ordrhoOut.Printf("%u %g %i %i\n", i+1, Points_[i].Density(), Points_[i].Fnum()+1,
Points_[i].Oidx()+1);
ordrhoOut.CloseFile();
// Determine minimum distances
int first_idx = Points_[0].Oidx();
Points_[first_idx].SetDist( -1.0 );
Points_[first_idx].SetNearestIdx(-1);
for (unsigned int ii = 1; ii != Points_.size(); ii++) {
int ord_i = Points_[ii].Oidx();
Points_[ord_i].SetDist( maxDist );
for (unsigned int jj = 0; jj != ii; jj++) {
int ord_j = Points_[jj].Oidx();
double dist = FrameDistances_.GetFdist(Points_[ord_i].Fnum(), Points_[ord_j].Fnum());
if (dist < Points_[ord_i].Dist()) {
Points_[ord_i].SetDist( dist );
Points_[ord_j].SetNearestIdx( ord_j );
}
}
}
if (!dvdfile_.empty()) {
CpptrajFile output;
if (output.OpenWrite(dvdfile_)) return 1;
for (Carray::const_iterator point = Points_.begin(); point != Points_.end(); ++point)
output.Printf("%g %g %i\n", point->Density(), point->Dist(), point->NearestIdx()+1);
output.CloseFile();
}
return 0;
}
/**
Gets vv vector normalized
*/
Cpoint Cline::getDirection() const
{
return Cpoint(vv.get_xx()/length, vv.get_yy()/length);
}