コード例 #1
0
ファイル: SequenceAlign.cpp プロジェクト: jcr13/cpptraj
int SequenceAlign(CpptrajState& State, ArgList& argIn) {
  std::string blastfile = argIn.GetStringKey("blastfile");
  if (blastfile.empty()) {
    mprinterr("Error: 'blastfile' must be specified.\n");
    return 1;
  }
  ReferenceFrame qref = State.DSL()->GetReferenceFrame(argIn);
  if (qref.error() || qref.empty()) {
    mprinterr("Error: Must specify reference structure for query.\n");
    return 1;
  }
  std::string outfilename = argIn.GetStringKey("out");
  if (outfilename.empty()) {
    mprinterr("Error: Must specify output file.\n");
    return 1;
  }
  TrajectoryFile::TrajFormatType fmt = TrajectoryFile::GetFormatFromArg(argIn);
  if (fmt != TrajectoryFile::PDBFILE && fmt != TrajectoryFile::MOL2FILE)
    fmt = TrajectoryFile::PDBFILE; // Default to PDB
  int smaskoffset = argIn.getKeyInt("smaskoffset", 0) + 1;
  int qmaskoffset = argIn.getKeyInt("qmaskoffset", 0) + 1;

  // Load blast file
  mprintf("\tReading BLAST alignment from '%s'\n", blastfile.c_str());
  BufferedLine infile;
  if (infile.OpenFileRead( blastfile )) return 1;
  // Seek down to first Query line.
  const char* ptr = infile.Line();
  bool atFirstQuery = false;
  while (ptr != 0) {
    if (*ptr == 'Q') {
      if ( strncmp(ptr, "Query", 5) == 0 ) {
        atFirstQuery = true;
        break;
      }
    }
    ptr = infile.Line();
  }
  if (!atFirstQuery) {
    mprinterr("Error: 'Query' not found.\n");
    return 1;
  }

  // Read alignment. Replacing query with subject.
  typedef std::vector<char> Carray;
  typedef std::vector<int> Iarray;
  Carray Query; // Query residues
  Carray Sbjct; // Sbjct residues
  Iarray Smap;  // Smap[Sbjct index] = Query index
  while (ptr != 0) {
    const char* qline = ptr;           // query line
    const char* aline = infile.Line(); // alignment line
    const char* sline = infile.Line(); // subject line
    if (aline == 0 || sline == 0) {
      mprinterr("Error: Missing alignment line or subject line after Query:\n");
      mprinterr("Error:  %s", qline);
      return 1;
    }
    for (int idx = 12; qline[idx] != ' '; idx++) {
      if (qline[idx] == '-') {
        // Sbjct does not have corresponding res in Query
        Smap.push_back(-1);
        Sbjct.push_back( sline[idx] );
      } else if (sline[idx] == '-') {
        // Query does not have a corresponding res in Sbjct
        Query.push_back( qline[idx] );
      } else {
        // Direct Query to Sbjct map
        Smap.push_back( Query.size() );
        Sbjct.push_back( sline[idx] );
        Query.push_back( qline[idx] );
      }
    }
    // Scan to next Query 
    ptr = infile.Line();
    while (ptr != 0) {
      if (*ptr == 'Q') {
        if ( strncmp(ptr, "Query", 5) == 0 ) break;
      }
      ptr = infile.Line();
    }
  }
  // DEBUG
  std::string SmaskExp, QmaskExp;
  if (State.Debug() > 0) mprintf("  Map of Sbjct to Query:\n");
  for (int sres = 0; sres != (int)Sbjct.size(); sres++) {
    if (State.Debug() > 0)
      mprintf("%-i %3s %i", sres+smaskoffset, Residue::ConvertResName(Sbjct[sres]),
              Smap[sres]+qmaskoffset);
    const char* qres = "";
    if (Smap[sres] != -1) {
      qres = Residue::ConvertResName(Query[Smap[sres]]);
      if (SmaskExp.empty())
        SmaskExp.assign( integerToString(sres+smaskoffset) );
      else
        SmaskExp.append( "," + integerToString(sres+smaskoffset) );
      if (QmaskExp.empty())
        QmaskExp.assign( integerToString(Smap[sres]+qmaskoffset) );
      else
        QmaskExp.append( "," + integerToString(Smap[sres]+qmaskoffset) );

    }
    if (State.Debug() > 0) mprintf(" %3s\n", qres);
  }
  mprintf("Smask: %s\n", SmaskExp.c_str());
  mprintf("Qmask: %s\n", QmaskExp.c_str());
  // Check that query residues match reference.
  for (unsigned int sres = 0; sres != Sbjct.size(); sres++) {
    int qres = Smap[sres];
    if (qres != -1) {
      if (Query[qres] != qref.Parm().Res(qres).SingleCharName()) {
        mprintf("Warning: Potential residue mismatch: Query %s reference %s\n",
                Residue::ConvertResName(Query[qres]), qref.Parm().Res(qres).c_str());
      }
    }
  }
  // Build subject using coordinate from reference.
  //AtomMask sMask; // Contain atoms that should be in sTop
  Topology sTop;
  Frame sFrame;
  Iarray placeHolder; // Atom indices of placeholder residues.
  for (unsigned int sres = 0; sres != Sbjct.size(); sres++) {
    int qres = Smap[sres];
    NameType SresName( Residue::ConvertResName(Sbjct[sres]) );
    if (qres != -1) {
      Residue const& QR = qref.Parm().Res(qres);
      Residue SR(SresName, sres+1, ' ', QR.ChainID());
      if (Query[qres] == Sbjct[sres]) { // Exact match. All non-H atoms.
        for (int qat = QR.FirstAtom(); qat != QR.LastAtom(); qat++)
        {
          if (qref.Parm()[qat].Element() != Atom::HYDROGEN)
            sTop.AddTopAtom( qref.Parm()[qat], SR );
            sFrame.AddXYZ( qref.Coord().XYZ(qat) );
            //sMask.AddAtom(qat);
        }
      } else { // Partial match. Copy only backbone and CB.
        for (int qat = QR.FirstAtom(); qat != QR.LastAtom(); qat++)
        {
          if ( qref.Parm()[qat].Name().Match("N" ) ||
               qref.Parm()[qat].Name().Match("CA") ||
               qref.Parm()[qat].Name().Match("CB") ||
               qref.Parm()[qat].Name().Match("C" ) ||
               qref.Parm()[qat].Name().Match("O" ) )
          {
            sTop.AddTopAtom( qref.Parm()[qat], SR );
            sFrame.AddXYZ( qref.Coord().XYZ(qat) );
          }
        }
      }
    } else {
      // Residue in query does not exist for subject. Just put placeholder CA for now.
      Vec3 Zero(0.0);
      placeHolder.push_back( sTop.Natom() );
      sTop.AddTopAtom( Atom("CA", "C "), Residue(SresName, sres+1, ' ', ' ') );
      sFrame.AddXYZ( Zero.Dptr() );
    }
  }
  //sTop.PrintAtomInfo("*");
  mprintf("\tPlaceholder residue indices:");
  for (Iarray::const_iterator p = placeHolder.begin(); p != placeHolder.end(); ++p)
    mprintf(" %i", *p + 1);
  mprintf("\n");
  // Try to give placeholders more reasonable coordinates.
  if (!placeHolder.empty()) {
    Iarray current_indices;
    unsigned int pidx = 0;
    while (pidx < placeHolder.size()) {
      if (current_indices.empty()) {
        current_indices.push_back( placeHolder[pidx++] );
        // Search for the end of this segment
        for (; pidx != placeHolder.size(); pidx++) {
          if (placeHolder[pidx] - current_indices.back() > 1) break;
          current_indices.push_back( placeHolder[pidx] );
        }
        // DEBUG
        mprintf("\tSegment:");
        for (Iarray::const_iterator it = current_indices.begin();
                                    it != current_indices.end(); ++it)
          mprintf(" %i", *it + 1);
        // Get coordinates of residues bordering segment.
        int prev_res = sTop[current_indices.front()].ResNum() - 1;
        int next_res = sTop[current_indices.back() ].ResNum() + 1;
        mprintf(" (prev_res=%i, next_res=%i)\n", prev_res+1, next_res+1);
        Vec3 prev_crd(sFrame.XYZ(current_indices.front() - 1));
        Vec3 next_crd(sFrame.XYZ(current_indices.back()  + 1));
        prev_crd.Print("prev_crd");
        next_crd.Print("next_crd");
        Vec3 crd_step = (next_crd - prev_crd) / (double)(current_indices.size()+1);
        crd_step.Print("crd_step");
        double* xyz = sFrame.xAddress() + (current_indices.front() * 3);
        for (unsigned int i = 0; i != current_indices.size(); i++, xyz += 3) {
          prev_crd += crd_step;
          xyz[0] = prev_crd[0];
          xyz[1] = prev_crd[1];
          xyz[2] = prev_crd[2];
        }
        current_indices.clear();
      }
    }
  }
  //Topology* sTop = qref.Parm().partialModifyStateByMask( sMask );
  //if (sTop == 0) return 1;
  //Frame sFrame(qref.Coord(), sMask);
  // Write output traj
  Trajout_Single trajout;
  if (trajout.PrepareTrajWrite(outfilename, argIn, &sTop, CoordinateInfo(), 1, fmt)) return 1;
  if (trajout.WriteSingle(0, sFrame)) return 1;
  trajout.EndTraj();
  return 0;
}
コード例 #2
0
ファイル: Cluster_DPeaks.cpp プロジェクト: rmcgibbo/cpptraj
int Cluster_DPeaks::ChoosePointsAutomatically() {
  // Right now all density values are discrete. Try to choose outliers at each
  // value for which there is density.;
/*
  // For each point, calculate average distance (X,Y) to points in next and
  // previous density values.
  const double dens_cut = 3.0 * 3.0;
  const double dist_cut = 1.32 * 1.32;
  for (Carray::const_iterator point0 = Points_.begin(); point0 != Points_.end(); ++point0)
  {
    int Npts = 0;
    for (Carray::const_iterator point1 = Points_.begin(); point1 != Points_.end(); ++point1)
    {
      if (point0 != point1) {
        // Only do this for close densities
        double dX = (double)(point0->PointsWithinEps() - point1->PointsWithinEps());
        double dX2 = dX * dX;
        double dY = (point0->Dist() - point1->Dist());
        double dY2 = dY * dY;
        if (dX2 < dens_cut && dY2 < dist_cut) {
          Npts++;
        }
      }
    }
    mprintf("%i %i %i\n", point0->PointsWithinEps(), point0->Fnum()+1, Npts);
  }
*/

/*
  CpptrajFile tempOut;
  tempOut.OpenWrite("temp.dat");
  int currentDensity = -1;
  double distAv = 0.0;
  double distSD = 0.0;
  double sumWts = 0.0;
  int nValues = 0;
  Carray::const_iterator lastPoint = Points_.end() + 1;
  for (Carray::const_iterator point = Points_.begin(); point != lastPoint; ++point)
  {
    if (point == Points_.end() || point->PointsWithinEps() != currentDensity) {
      if (nValues > 0) {
        distAv = distAv / sumWts; //(double)nValues;
        distSD = (distSD / sumWts) - (distAv * distAv);
        if (distSD > 0.0)
          distSD = sqrt(distSD);
        else
          distSD = 0.0;
        //mprintf("Density %i: %i values  Avg= %g  SD= %g  SumWts= %g\n", currentDensity,
        //        nValues, distAv, distSD, sumWts);
        tempOut.Printf("%i %g\n", currentDensity, distAv);
      }
      if (point == Points_.end()) break;
      currentDensity = point->PointsWithinEps();
      distAv = 0.0;
      distSD = 0.0;
      sumWts = 0.0;
      nValues = 0;
    }
    double wt = exp(point->Dist());
    double dval = point->Dist() * wt;
    sumWts += wt;
    distAv += dval;
    distSD += (dval * dval);
    nValues++;
  }
  tempOut.CloseFile(); 
*/

  // BEGIN CALCULATING WEIGHTED DISTANCE AVERAGE
  CpptrajFile tempOut;
  tempOut.OpenWrite("temp.dat");
  DataSet_Mesh weightedAverage;
  Carray::const_iterator cp = Points_.begin();
  // Skip local density of 0.
  //while (cp->PointsWithinEps() == 0 && cp != Points_.end()) ++cp;
  while (cp != Points_.end())
  {
    int densityVal = cp->PointsWithinEps();
    Carray densityArray;
    // Add all points of current density.
    while (cp->PointsWithinEps() == densityVal && cp != Points_.end())
      densityArray.push_back( *(cp++) );
    mprintf("Density value %i has %zu points.\n", densityVal, densityArray.size());
    // Sort array by distance
    std::sort(densityArray.begin(), densityArray.end(), Cpoint::dist_sort());
    // Take the average of the points weighted by their position. 
    double wtDistAv = 0.0;
    double sumWts = 0.0;
    //std::vector<double> weights;
    //weights.reserve( densityArray.size() );
    int maxPt = (int)densityArray.size() - 1;
    for (int ip = 0; ip != (int)densityArray.size(); ++ip) 
    {
      double wt = exp( (double)(ip - maxPt) );
      //mprintf("\t%10i %10u %10u %10g\n", densityVal, ip, maxPt, wt);
      wtDistAv += (densityArray[ip].Dist() * wt);
      sumWts += wt;
      //weights.push_back( wt );
    }
    wtDistAv /= sumWts;
    // Calculate the weighted sample variance
    //double distSD = 0.0;
    //for (unsigned int ip = 0; ip != densityArray.size(); ++ip) {
    //  double diff = densityArray[ip].Dist() - wtDistAv;
    //  distSD += weights[ip] * (diff * diff);
    //}
    //distSD /= sumWts;
    weightedAverage.AddXY(densityVal, wtDistAv); 
    //tempOut.Printf("%i %g %g %g\n", densityVal, wtDistAv, sqrt(distSD), sumWts);
    tempOut.Printf("%i %g %g\n", densityVal, wtDistAv, sumWts);
/*
    // Find the median.
    double median, Q1, Q3;
    if (densityArray.size() == 1) {
      median = densityArray[0].Dist();
      Q1 = median;
      Q3 = median;
    } else {
      unsigned int q3_beg;
      unsigned int med_idx = densityArray.size() / 2; // Always 0 <= Q1 < med_idx
      if ((densityArray.size() % 2) == 0) {
        median = (densityArray[med_idx].Dist() + densityArray[med_idx-1].Dist()) / 2.0;
        q3_beg = med_idx;
      } else {
        median = densityArray[med_idx].Dist();
        q3_beg = med_idx + 1;
      }
      if (densityArray.size() == 2) {
        Q1 = densityArray[0].Dist();
        Q3 = densityArray[1].Dist();
      } else {
        // Find lower quartile
        unsigned int q1_idx = med_idx / 2;
        if ((med_idx % 2) == 0)
          Q1 = (densityArray[q1_idx].Dist() + densityArray[q1_idx-1].Dist()) / 2.0;
        else
          Q1 = densityArray[q1_idx].Dist();
        // Find upper quartile
        unsigned int q3_size = densityArray.size() - q3_beg;
        unsigned int q3_idx = (q3_size / 2) + q3_beg;
        if ((q3_size %2) == 0)
          Q3 = (densityArray[q3_idx].Dist() + densityArray[q3_idx-1].Dist()) / 2.0;
        else
          Q3 = densityArray[q3_idx].Dist();
      }
    }
    mprintf("\tMedian dist value is %g. Q1= %g   Q3= %g\n", median, Q1, Q3);
*/
  }
  tempOut.CloseFile();
  // END CALCULATING WEIGHTED DISTANCE AVERAGE

/*
  // TEST
  tempOut.OpenWrite("temp2.dat");
  std::vector<double> Hist( Points_.back().PointsWithinEps()+1, 0.0 );
  int gWidth = 3;
  double cval = 3.0;
  double two_c_squared = 2.0 * cval * cval;
  mprintf("DBG: cval= %g, Gaussian denominator is %g\n", cval, two_c_squared);
  for (int wtIdx = 0; wtIdx != (int)weightedAverage.Size(); wtIdx++)
  {
    int bval = weightedAverage.X(wtIdx);
    for (int xval = std::max(bval - gWidth, 0);
             xval != std::min(bval + gWidth + 1, (int)Hist.size()); xval++)
    {
      // a: height (weighted average)
      // b: center (density value)
      // c: width
      // x: density value in histogram 
      //int xval = weightedAverage.X(idx);
      //double bval = weightedAverage.X(wtIdx);
      //double bval = (double)wtIdx;
      double diff = (double)(xval - bval);
      //Hist[xval] += (weightedAverage.Y(wtIdx) * exp( -( (diff * diff) / two_c_squared ) ));
      Hist[xval] = std::max(Hist[xval],
                            weightedAverage.Y(wtIdx) * exp( -( (diff * diff) / two_c_squared ) ));
    }
  }
  for (unsigned int idx = 0; idx != Hist.size(); idx++)
    tempOut.Printf("%u %g\n", idx, Hist[idx]);
  tempOut.CloseFile();
  // END TEST
*/
/*
  // TEST
  // Construct best-fit line segments
  tempOut.OpenWrite("temp2.dat");
  double slope, intercept, correl;
  int segment_length = 3;
  DataSet_Mesh Segment;
  Segment.Allocate1D( segment_length );
  for (int wtIdx = 0; wtIdx != (int)weightedAverage.Size(); wtIdx++)
  {
    Segment.Clear();
    for (int idx = std::max(wtIdx - 1, 0); // TODO: use segment_length
             idx != std::min(wtIdx + 2, (int)weightedAverage.Size()); idx++)
        Segment.AddXY(weightedAverage.X(idx), weightedAverage.Y(idx));
    Segment.LinearRegression(slope, intercept, correl, true);
    for (int idx = std::max(wtIdx - 1, 0); // TODO: use segment_length
             idx != std::min(wtIdx + 2, (int)weightedAverage.Size()); idx++)
    {
      double x = weightedAverage.X(idx);
      double y = slope * x + intercept;
      tempOut.Printf("%g %g %i\n", x, y, weightedAverage.X(wtIdx));
    }
  }
  tempOut.CloseFile(); 
  // END TEST
*/

  // BEGIN WEIGHTED RUNNING AVG/SD OF DISTANCES
  // For each point, determine if it is greater than the average of the
  // weighted average distances of the previous, current, and next densities.
  int width = 2;
  int currentDensity = 0;
  int wtIdx = 0;
  double currentAvg = 0.0;
  double deltaSD = 0.0;
  double deltaAv = 0.0;
  int    Ndelta = 0;
  CpptrajFile raOut;
  if (!rafile_.empty()) raOut.OpenWrite(rafile_);
  CpptrajFile raDelta;
  if (!radelta_.empty()) raDelta.OpenWrite(radelta_);
  std::vector<unsigned int> candidateIdxs;
  std::vector<double> candidateDeltas;
  cp = Points_.begin();
  // Skip over points with zero density
  while (cp != Points_.end() && cp->PointsWithinEps() == 0) ++cp;
  while (weightedAverage.X(wtIdx) != cp->PointsWithinEps() && wtIdx < (int)Points_.size())
    ++wtIdx;
  for (Carray::const_iterator point = cp; point != Points_.end(); ++point)
  {
    if (point->PointsWithinEps() != currentDensity) {
      //currentAvg = weightedAverage.Y(wtIdx);
      // New density value. Determine average.
      currentAvg = 0.0;
     // unsigned int Npt = 0; 
      double currentWt = 0.0;
      for (int idx = std::max(wtIdx - width, 0);
               idx != std::min(wtIdx + width + 1, (int)weightedAverage.Size()); idx++)
      {
        //currentAvg += weightedAverage.Y(idx);
        //Npt++;
        double wt = weightedAverage.Y(idx);
        currentAvg += (weightedAverage.Y(idx) * wt);
        currentWt += wt;
      }
      //currentAvg /= (double)Npt;
      currentAvg /= currentWt;
      //smoothAv += currentAvg;
      //smoothSD += (currentAvg * currentAvg);
      //Nsmooth++;
      currentDensity = point->PointsWithinEps();
      if (raOut.IsOpen())
        raOut.Printf("%i %g %g\n", currentDensity, currentAvg, weightedAverage.Y(wtIdx));
      wtIdx++;
    }
    double delta = (point->Dist() - currentAvg);
    if (delta > 0.0) {
      //delta *= log((double)currentDensity);
      if (raDelta.IsOpen())
        raDelta.Printf("%8i %8.3f %8i %8.3f %8.3f\n",
                       currentDensity, delta, point->Fnum()+1, point->Dist(), currentAvg);
      candidateIdxs.push_back( point - Points_.begin() );
      candidateDeltas.push_back( delta );
      deltaAv += delta;
      deltaSD += (delta * delta);
      Ndelta++;
    }
  }
  raOut.CloseFile();
  deltaAv /= (double)Ndelta;
  deltaSD = (deltaSD / (double)Ndelta) - (deltaAv * deltaAv);
  if (deltaSD > 0.0)
    deltaSD = sqrt(deltaSD);
  else
    deltaSD = 0.0;
  if (raDelta.IsOpen())
    raDelta.Printf("#DeltaAvg= %g  DeltaSD= %g\n", deltaAv, deltaSD);
  raDelta.CloseFile();
  int cnum = 0;
  for (unsigned int i = 0; i != candidateIdxs.size(); i++) {
    if (candidateDeltas[i] > (deltaSD)) {
      Points_[candidateIdxs[i]].SetCluster( cnum++ );
      mprintf("\tPoint %u (frame %i, density %i) selected as candidate for cluster %i\n",
              candidateIdxs[i], Points_[candidateIdxs[i]].Fnum()+1,
              Points_[candidateIdxs[i]].PointsWithinEps(), cnum-1);
    }
  }
  // END WEIGHTED AVG/SD OF DISTANCES

/* 
  // Currently doing this by calculating the running average of density vs 
  // distance, then choosing points with distance > twice the SD of the 
  // running average.
  // NOTE: Store in a mesh data set for now in case we want to spline etc later.
  if (avg_factor_ < 1) avg_factor_ = 10; 
  unsigned int window_size = Points_.size() / (unsigned int)avg_factor_;
  mprintf("\tRunning avg window size is %u\n", window_size);
  // FIXME: Handle case where window_size < frames
  DataSet_Mesh runavg;
  unsigned int ra_size = Points_.size() - window_size + 1;
  runavg.Allocate1D( ra_size );
  double dwindow = (double)window_size;
  double sumx = 0.0;
  double sumy = 0.0;
  for (unsigned int i = 0; i < window_size; i++) {
    sumx += (double)Points_[i].PointsWithinEps();
    sumy += Points_[i].Dist();
  }
  runavg.AddXY( sumx / dwindow, sumy / dwindow );
  for (unsigned int i = 1; i < ra_size; i++) {
    unsigned int nextwin = i + window_size - 1;
    unsigned int prevwin = i - 1;
    sumx = (double)Points_[nextwin].PointsWithinEps() -
           (double)Points_[prevwin].PointsWithinEps() + sumx;
    sumy =         Points_[nextwin].Dist()    -
                   Points_[prevwin].Dist()    + sumy;
    runavg.AddXY( sumx / dwindow, sumy / dwindow );
  }
  // Write running average
  if (!rafile_.empty()) {
    CpptrajFile raOut;
    if (raOut.OpenWrite(rafile_))
      mprinterr("Error: Could not open running avg file '%s' for write.\n", rafile_.c_str());
    else {
      for (unsigned int i = 0; i != runavg.Size(); i++)
        raOut.Printf("%g %g\n", runavg.X(i), runavg.Y(i));
      raOut.CloseFile();
    }
  }
  double ra_sd;
  double ra_avg = runavg.Avg( ra_sd );
  // Double stdev to use as cutoff for findning anomalously high peaks.
  ra_sd *= 2.0;
  mprintf("\tAvg of running avg set is %g, SD*2.0 (delta cutoff) is %g\n", ra_avg, ra_sd);
  // For each point in density vs distance plot, determine which running
  // average point is closest. If the difference between the point and the
  // running average point is > 2.0 the SD of the running average data,
  // consider it a 'peak'. 
  CpptrajFile raDelta;
  if (!radelta_.empty())
    raDelta.OpenWrite("radelta.dat");
  if (raDelta.IsOpen())
    raDelta.Printf("%-10s %10s %10s\n", "#Frame", "RnAvgPos", "Delta");
  unsigned int ra_position = 0; // Position in the runavg DataSet
  unsigned int ra_end = runavg.Size() - 1;
  int cnum = 0;
  for (Carray::iterator point = Points_.begin();
                        point != Points_.end(); ++point)
  {
    if (ra_position != ra_end) {
      // Is the next running avgd point closer to this point?
      while (ra_position != ra_end) {
        double dens  = (double)point->PointsWithinEps();
        double diff0 = fabs( dens - runavg.X(ra_position  ) );
        double diff1 = fabs( dens - runavg.X(ra_position+1) );
        if (diff1 < diff0)
          ++ra_position; // Next running avg position is closer for this point.
        else
          break; // This position is closer.
      }
    }
    double delta = point->Dist() - runavg.Y(ra_position);
    if (raDelta.IsOpen())
      raDelta.Printf("%-10i %10u %10g", point->Fnum()+1, ra_position, delta);
    if (delta > ra_sd) {
      if (raDelta.IsOpen())
        raDelta.Printf(" POTENTIAL CLUSTER %i", cnum);
      point->SetCluster(cnum++);
    }
    if (raDelta.IsOpen()) raDelta.Printf("\n");
  }
  raDelta.CloseFile();
*/
  return cnum;
}