예제 #1
0
/** For each point p, calculate function Kdist(p) which is the distance of
  * the Kth nearest point to p.
  */
void Cluster_DBSCAN::ComputeKdist( int Kval, std::vector<int> const& FramesToCluster ) const {
  std::vector<double> dists;
  std::vector<double> Kdist;
  dists.reserve( FramesToCluster.size() ); 
  Kdist.reserve( FramesToCluster.size() );
  std::string outfilename = k_prefix_ + "Kdist." + integerToString(Kval) + ".dat";
  mprintf("\tDBSCAN: Calculating Kdist(%i), output to %s\n", Kval, outfilename.c_str());
  for (std::vector<int>::const_iterator point = FramesToCluster.begin();
                                        point != FramesToCluster.end();
                                        ++point)
  {
    // Store distances from this point
    dists.clear();
    for (std::vector<int>::const_iterator otherpoint = FramesToCluster.begin();
                                          otherpoint != FramesToCluster.end();
                                          ++otherpoint)
      dists.push_back( FrameDistances_.GetFdist(*point, *otherpoint) );
    // Sort distances - first dist should always be 0
    std::sort(dists.begin(), dists.end());
    Kdist.push_back( dists[Kval] );
  }
  std::sort( Kdist.begin(), Kdist.end() );
  CpptrajFile Outfile;
  Outfile.OpenWrite(outfilename);
  Outfile.Printf("%-8s %1i%-11s\n", "#Point", Kval,"-dist");
  // Write out largest to smallest
  unsigned int ik = 0;
  for (std::vector<double>::reverse_iterator k = Kdist.rbegin(); 
                                             k != Kdist.rend(); ++k, ++ik)
    Outfile.Printf("%8u %12.4f\n", ik, *k);
  Outfile.CloseFile();
}
예제 #2
0
// DataIO_Std::WriteData()
int DataIO_Std::WriteData(FileName const& fname, DataSetList const& SetList)
{
  int err = 0;
  if (!SetList.empty()) {
    // Open output file.
    CpptrajFile file;
    if (file.OpenWrite( fname )) return 1;
    // Base write type off first data set dimension FIXME
    if (SetList[0]->Group() == DataSet::CLUSTERMATRIX) {
      // Special case of 2D - may have sieved frames.
      err = WriteCmatrix(file, SetList);
    } else if (SetList[0]->Ndim() == 1) {
      if (group_ == NO_TYPE) {
        if (isInverted_)
          err = WriteDataInverted(file, SetList);
        else
          err = WriteDataNormal(file, SetList);
      } else
        err = WriteByGroup(file, SetList, group_);
    } else if (SetList[0]->Ndim() == 2)
      err = WriteData2D(file, SetList);
    else if (SetList[0]->Ndim() == 3)
      err = WriteData3D(file, SetList);
    file.CloseFile();
  }
  return err;
}
예제 #3
0
// TODO: Accept const ArgList so arguments are not reset?
CpptrajFile* DataFileList::AddCpptrajFile(FileName const& nameIn, 
                                          std::string const& descrip,
                                          CFtype typeIn, bool allowStdout)
{
  // If no filename and stdout not allowed, no output desired.
  if (nameIn.empty() && !allowStdout) return 0;
  FileName name;
  CpptrajFile* Current = 0;
  int currentIdx = -1;
  if (!nameIn.empty()) {
    name = nameIn;
    // Append ensemble number if set.
    if (ensembleNum_ != -1)
      name.Append( "." + integerToString(ensembleNum_) );
    // Check if filename in use by DataFile.
    DataFile* df = GetDataFile(name);
    if (df != 0) {
      mprinterr("Error: Text output file name '%s' already in use by data file '%s'.\n",
                nameIn.full(), df->DataFilename().full());
      return 0;
    }
    // Check if this filename already in use
    currentIdx = GetCpptrajFileIdx( name );
    if (currentIdx != -1) Current = cfList_[currentIdx];
  }
  // If no CpptrajFile associated with name, create new CpptrajFile
  if (Current==0) {
    switch (typeIn) {
      case TEXT: Current = new CpptrajFile(); break;
      case PDB:  Current = (CpptrajFile*)(new PDBfile()); break;
    }
    Current->SetDebug(debug_);
    // Set up file for writing. 
    //if (Current->SetupWrite( name, debug_ ))
    if (Current->OpenWrite( name ))
    {
      mprinterr("Error: Setting up text output file %s\n", name.full());
      delete Current;
      return 0;
    }
    cfList_.push_back( Current );
    cfData_.push_back( CFstruct(descrip, typeIn) );
  } else {
    // If Current type does not match typeIn do not allow.
    if (typeIn != cfData_[currentIdx].Type()) {
      mprinterr("Error: Cannot change type of text output for '%s'.\n", Current->Filename().full());
      return 0;
    }
    Current->SetDebug(debug_);
    // Update description
    if (!descrip.empty())
      cfData_[currentIdx].UpdateDescrip( descrip );
  }
  return Current;
}
예제 #4
0
// DataIO_CCP4::WriteData()
int DataIO_CCP4::WriteData(FileName const& fname, DataSetList const& setList)
{
    // Open output file
    CpptrajFile outfile;
    if (outfile.OpenWrite(fname)) {
        mprinterr("Error: Could not open CCP4 output file '%s'.\n", fname.full());
        return 1;
    }
    // Warn about writing multiple sets
    if (setList.size() > 1)
        mprintf("Warning: %s: Writing multiple 3D sets in CCP4 format not supported.\n"
                "Warning:   Only writing first set.\n", fname.full());
    return WriteSet3D( setList.begin(), outfile );
}
예제 #5
0
// DataIO_OpenDx::WriteData()
int DataIO_OpenDx::WriteData(FileName const& fname, DataSetList const& setList)
{
  // Open output file
  CpptrajFile outfile;
  if (outfile.OpenWrite(fname)) {
    mprinterr("Error: Could not open OpenDX output file.\n");
    return 1;
  }
  // Warn about writing multiple sets
  if (setList.size() > 1)
    mprintf("Warning: %s: Writing multiple 3D sets in OpenDX format may result in unexpected behavior\n", fname.full());
  int err = 0;
  for (DataSetList::const_iterator set = setList.begin(); set != setList.end(); ++set)
    err += WriteSet3D( *(*set), outfile );
  return err;
}
예제 #6
0
void Action_Pairwise::Print() {
  if (nframes_ < 1) return;
  // Divide matrices by # of frames
  double norm = 1.0 / (double)nframes_;
  for (unsigned int i = 0; i != vdwMat_->Size(); i++)
  {
    (*vdwMat_)[i] *= norm;
    (*eleMat_)[i] *= norm;
  }
  // Write out final results
  CpptrajFile AvgOut;
  if (AvgOut.OpenWrite( avgout_ )) return;
  if (nb_calcType_ == NORMAL)
    mprintf("  PAIRWISE: Writing all pairs with |<evdw>| > %.4f, |<eelec>| > %.4f\n",
            cut_evdw_, cut_eelec_);
  else if (nb_calcType_ == COMPARE_REF)
    mprintf("  PAIRWISE: Writing all pairs with |<dEvdw>| > %.4f, |<dEelec>| > %.4f\n",
            cut_evdw_, cut_eelec_);
  AvgOut.Printf("%-16s %5s -- %16s %5s : ENE\n","#Name1", "At1", "Name2", "At2");
  for (AtomMask::const_iterator m1 = Mask0_.begin(); m1 != Mask0_.end(); ++m1) {
    for (AtomMask::const_iterator m2 = m1 + 1; m2 != Mask0_.end(); ++m2)
    {
      double EV = vdwMat_->GetElement(*m1, *m2);
      double EE = eleMat_->GetElement(*m1, *m2);
      bool outputv = ( fabs(EV) > cut_evdw_ );
      bool outpute = ( fabs(EE) > cut_eelec_ );
      if (outputv || outpute) {
        AvgOut.Printf("%16s %5i -- %16s %5i :",
                CurrentParm_->TruncResAtomName(*m1).c_str(), *m1 + 1,
                CurrentParm_->TruncResAtomName(*m2).c_str(), *m2 + 1);
        if (outputv) AvgOut.Printf("  EVDW= %12.5e", EV);
        if (outpute) AvgOut.Printf(" EELEC= %12.5e", EE);
        AvgOut.Printf("\n");
      }
    }
  }
}
예제 #7
0
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;
}
예제 #8
0
// -----------------------------------------------------------------------------
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;
}
예제 #9
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;
}
예제 #10
0
int Parm_CharmmPsf::WriteParm(FileName const& fname, Topology const& parm) {
  // TODO: CMAP etc info
  CpptrajFile outfile;
  if (outfile.OpenWrite(fname)) return 1;
  // Write PSF
  outfile.Printf("PSF\n\n");
  // Write title
  std::string titleOut = parm.ParmName();
  titleOut.resize(78);
  outfile.Printf("%8i !NTITLE\n* %-78s\n\n", 1, titleOut.c_str());
  // Write NATOM section
  outfile.Printf("%8i !NATOM\n", parm.Natom());
  unsigned int idx = 1;
  // Make fake segment ids for now.
  char segid[2];
  segid[0] = 'A';
  segid[1] = '\0';
  mprintf("Warning: Assigning single letter segment IDs.\n");
  int currentMol = 0;
  bool inSolvent = false;
  for (Topology::atom_iterator atom = parm.begin(); atom != parm.end(); ++atom, ++idx) {
    int resnum = atom->ResNum();
    if (atom->MolNum() != currentMol) {
      if (!inSolvent) {
        inSolvent = parm.Mol(atom->MolNum()).IsSolvent();
        currentMol = atom->MolNum();
        segid[0]++;
      } else
        inSolvent = parm.Mol(atom->MolNum()).IsSolvent();
    }
    // TODO: Print type name for xplor-like PSF
    int typeindex = atom->TypeIndex() + 1;
    // If type begins with digit, assume charmm numbers were read as
    // type. Currently Amber types all begin with letters.
    if (isdigit(atom->Type()[0]))
      typeindex = convertToInteger( *(atom->Type()) );
    // ATOM# SEGID RES# RES ATNAME ATTYPE CHRG MASS (REST OF COLUMNS ARE LIKELY FOR CMAP AND CHEQ)
    outfile.Printf("%8i %-4s %-4i %-4s %-4s %4i %14.6G %9g  %10i\n", idx, segid,
                   parm.Res(resnum).OriginalResNum(), parm.Res(resnum).c_str(),
                   atom->c_str(), typeindex, atom->Charge(),
                   atom->Mass(), 0);
  }
  outfile.Printf("\n");
  // Write NBOND section
  outfile.Printf("%8u !NBOND: bonds\n", parm.Bonds().size() + parm.BondsH().size());
  idx = 1;
  for (BondArray::const_iterator bond = parm.BondsH().begin();
                                 bond != parm.BondsH().end(); ++bond, ++idx)
  {
    outfile.Printf("%8i%8i", bond->A1()+1, bond->A2()+1);
    if ((idx % 4)==0) outfile.Printf("\n"); 
  }
  for (BondArray::const_iterator bond = parm.Bonds().begin();
                                 bond != parm.Bonds().end(); ++bond, ++idx)
  {
    outfile.Printf("%8i%8i", bond->A1()+1, bond->A2()+1);
    if ((idx % 4)==0) outfile.Printf("\n"); 
  }
  if ((idx % 4)!=0) outfile.Printf("\n");
  outfile.Printf("\n");
  // Write NTHETA section
  outfile.Printf("%8u !NTHETA: angles\n", parm.Angles().size() + parm.AnglesH().size());
  idx = 1;
  for (AngleArray::const_iterator ang = parm.AnglesH().begin();
                                  ang != parm.AnglesH().end(); ++ang, ++idx)
  {
    outfile.Printf("%8i%8i%8i", ang->A1()+1, ang->A2()+1, ang->A3()+1);
    if ((idx % 3)==0) outfile.Printf("\n");
  }
  for (AngleArray::const_iterator ang = parm.Angles().begin();
                                  ang != parm.Angles().end(); ++ang, ++idx)
  {
    outfile.Printf("%8i%8i%8i", ang->A1()+1, ang->A2()+1, ang->A3()+1);
    if ((idx % 3)==0) outfile.Printf("\n");
  }
  if ((idx % 3)==0) outfile.Printf("\n");
  outfile.Printf("\n");
  // Write out NPHI section
  outfile.Printf("%8u !NPHI: dihedrals\n", parm.Dihedrals().size() + parm.DihedralsH().size());
  idx = 1;
  for (DihedralArray::const_iterator dih = parm.DihedralsH().begin();
                                     dih != parm.DihedralsH().end(); ++dih, ++idx)
  {
    outfile.Printf("%8i%8i%8i%8i", dih->A1()+1, dih->A2()+1, dih->A3()+1, dih->A4()+1);
    if ((idx % 2)==0) outfile.Printf("\n");
  }
  for (DihedralArray::const_iterator dih = parm.Dihedrals().begin();
                                     dih != parm.Dihedrals().end(); ++dih, ++idx)
  {
    outfile.Printf("%8i%8i%8i%8i", dih->A1()+1, dih->A2()+1, dih->A3()+1, dih->A4()+1);
    if ((idx % 2)==0) outfile.Printf("\n");
  }
  if ((idx % 2)==0) outfile.Printf("\n");
  outfile.Printf("\n");

  outfile.CloseFile();
  return 0;
}
예제 #11
0
// Analysis_Wavelet::Analyze()
Analysis::RetType Analysis_Wavelet::Analyze() {
    // Step 1 - Create a matrix that is #atoms rows by #frames - 1 cols,
    //          where matrix(frame, atom) is the distance that atom has
    //          travelled from the previous frame.
    // TODO: Implement this in Action_Matrix()?
    mprintf("    WAVELET:\n");
    // First set up atom mask.
    if (coords_->Top().SetupIntegerMask( mask_ )) return Analysis::ERR;
    mask_.MaskInfo();
    int natoms = mask_.Nselected();
    int nframes = (int)coords_->Size();
    if (natoms < 1 || nframes < 2) {
        mprinterr("Error: Not enough frames (%i) or atoms (%i) in '%s'\n",
                  nframes, natoms, coords_->legend());
        return Analysis::ERR;
    }
    Matrix<double> d_matrix;
    mprintf("\t%i frames, %i atoms, distance matrix will require %.2f MB\n",
            (double)d_matrix.sizeInBytes(nframes, natoms) / (1024.0*1024.0));
    d_matrix.resize(nframes, natoms);
    // Get initial frame.
    Frame currentFrame, lastFrame;
    currentFrame.SetupFrameFromMask( mask_, coords_->Top().Atoms() );
    lastFrame = currentFrame;
    coords_->GetFrame( 0, lastFrame, mask_ );
    // Iterate over frames
    for (int frm = 1; frm != nframes; frm++) {
        coords_->GetFrame( frm, currentFrame, mask_ );
        int idx = frm; // Position in distance matrix; start at column 'frame'
        for (int at = 0; at != natoms; at++, idx += nframes)
            // Distance of atom in currentFrame from its position in lastFrame.
            d_matrix[idx] = sqrt(DIST2_NoImage( currentFrame.XYZ(at), lastFrame.XYZ(at) ));
        //lastFrame = currentFrame; // TODO: Re-enable?
    }
# ifdef DEBUG_WAVELET
    // DEBUG: Write matrix to file.
    CpptrajFile dmatrixOut; // DEBUG
    dmatrixOut.OpenWrite("dmatrix.dat");
    Matrix<double>::iterator mval = d_matrix.begin();
    for (int row = 0; row != natoms; row++) {
        for (int col = 0; col != nframes; col++)
            dmatrixOut.Printf("%g ", *(mval++));
        dmatrixOut.Printf("\n");
    }
    dmatrixOut.CloseFile();
# endif

    // Precompute some factors for calculating scaled wavelets.
    const double one_over_sqrt_N = 1.0 / sqrt(static_cast<double>( nframes ));
    std::vector<int> arrayK( nframes );
    arrayK[0] = -1 * (nframes/2);
    for (int i = 1; i != nframes; i++)
        arrayK[i] = arrayK[i-1] + 1;
# ifdef DEBUG_WAVELET
    mprintf("DEBUG: K:");
    for (std::vector<int>::const_iterator kval = arrayK.begin(); kval != arrayK.end(); ++kval)
        mprintf(" %i", *kval);
    mprintf("\n");
# endif

    // Step 2 - Get FFT of wavelet for each scale.
    PubFFT pubfft;
    pubfft.SetupFFTforN( nframes );
    mprintf("\tMemory required for scaled wavelet array: %.2f MB\n",
            (double)(2 * nframes * nb_ * sizeof(double)) / (1024 * 1024));
    typedef std::vector<ComplexArray> WaveletArray;
    WaveletArray FFT_of_Scaled_Wavelets;
    FFT_of_Scaled_Wavelets.reserve( nb_ );
    typedef std::vector<double> Darray;
    Darray scaleVector;
    scaleVector.reserve( nb_ );
    Darray MIN( nb_ * 2 );
    for (int iscale = 0; iscale != nb_; iscale++)
    {
        // Calculate and store scale factor.
        scaleVector.push_back( S0_ * pow(2.0, iscale * ds_) );
        // Populate MIN array
        MIN[iscale    ] = (0.00647*pow((correction_*scaleVector.back()),1.41344)+19.7527)*chival_;
        MIN[iscale+nb_] = correction_*scaleVector.back();
        // Calculate scalved wavelet
        ComplexArray scaledWavelet;
        switch (wavelet_type_) {
        case W_MORLET:
            scaledWavelet = F_Morlet(arrayK, scaleVector.back());
            break;
        case W_PAUL  :
            scaledWavelet = F_Paul(arrayK, scaleVector.back());
            break;
        case W_NONE  :
            return Analysis::ERR; // Sanity check
        }
#   ifdef DEBUG_WAVELET
        PrintComplex("wavelet_before_fft", scaledWavelet);
#   endif
        // Perform FFT
        pubfft.Forward( scaledWavelet );
        // Normalize
        scaledWavelet.Normalize( one_over_sqrt_N );
#   ifdef DEBUG_WAVELET
        PrintComplex("wavelet_after_fft", scaledWavelet);
#   endif
        FFT_of_Scaled_Wavelets.push_back( scaledWavelet );
    }
# ifdef DEBUG_WAVELET
    mprintf("DEBUG: Scaling factors:");
    for (Darray::const_iterator sval = scaleVector.begin(); sval != scaleVector.end(); ++sval)
        mprintf(" %g", *sval);
    mprintf("\n");
    mprintf("DEBUG: MIN:");
    for (int i = 0; i != nb_; i++)
        mprintf(" %g", MIN[i]);
    mprintf("\n");
# endif

    // Step 3 - For each atom, calculate the convolution of scaled wavelets
    //          with rows (atom distance vs frame) via dot product of the
    //          frequency domains, i.e. Fourier-transformed, followed by an
    //          inverse FT.
    DataSet_MatrixFlt& OUT = static_cast<DataSet_MatrixFlt&>( *output_ );
    mprintf("\tMemory required for output matrix: %.2f MB\n",
            (double)Matrix<float>::sizeInBytes(nframes, natoms)/(1024.0*1024.0));
    OUT.Allocate2D( nframes, natoms ); // Should initialize to zero
    Matrix<double> MAX;
    mprintf("\tMemory required for Max array: %.2f MB\n",
            (double)MAX.sizeInBytes(nframes, natoms)/(1024.0*1024.0));
    MAX.resize( nframes, natoms );
    Darray magnitude( nframes ); // Scratch space for calculating magnitude across rows
    for (int at = 0; at != natoms; at++) {
        ComplexArray AtomSignal( nframes ); // Initializes to zero
        // Calculate the distance variance for this atom and populate the array.
        int midx = at * nframes; // Index into d_matrix
        int cidx = 0;            // Index into AtomSignal
        double d_avg = 0.0;
        double d_var = 0.0;
        for (int frm = 0; frm != nframes; frm++, cidx += 2, midx++) {
            d_avg += d_matrix[midx];
            d_var += (d_matrix[midx] * d_matrix[midx]);
            AtomSignal[cidx] = d_matrix[midx];
        }
        d_var = (d_var - ((d_avg * d_avg) / (double)nframes)) / ((double)(nframes - 1));
#   ifdef DEBUG_WAVELET
        mprintf("VARIANCE: %g\n", d_var);
#   endif
        double var_norm = 1.0 / d_var;
        // Calculate FT of atom signal
        pubfft.Forward( AtomSignal );
#   ifdef DEBUG_WAVELET
        PrintComplex("AtomSignal", AtomSignal);
#   endif
        // Normalize
        AtomSignal.Normalize( one_over_sqrt_N );
        // Calculate dot product of atom signal with each scaled FT wavelet
        for (int iscale = 0; iscale != nb_; iscale++) {
            ComplexArray dot = AtomSignal.TimesComplexConj( FFT_of_Scaled_Wavelets[iscale] );
            // Inverse FT of dot product
            pubfft.Back( dot );
#     ifdef DEBUG_WAVELET
            PrintComplex("InverseFT_Dot", dot);
#     endif
            // Chi-squared testing
            midx = at * nframes;
            cidx = 0;
            for (int frm = 0; frm != nframes; frm++, cidx += 2, midx++) {
                magnitude[frm] = (dot[cidx]*dot[cidx] + dot[cidx+1]*dot[cidx+1]) * var_norm;
                if (magnitude[frm] < MIN[iscale])
                    magnitude[frm] = 0.0;
                if (magnitude[frm] > MAX[midx]) {
                    MAX[midx] = magnitude[frm];
                    //Indices[midx] = iscale
                    OUT[midx] = (float)(correction_ * scaleVector[iscale]);
                }
            }
#     ifdef DEBUG_WAVELET
            mprintf("DEBUG: AbsoluteValue:");
            for (Darray::const_iterator dval = magnitude.begin(); dval != magnitude.end(); ++dval)
                mprintf(" %g", *dval);
            mprintf("\n");
#     endif
        } // END loop over scales
    } // END loop over atoms
# ifdef DEBUG_WAVELET
    // DEBUG: Print MAX
    CpptrajFile maxmatrixOut; // DEBUG
    maxmatrixOut.OpenWrite("maxmatrix.dat");
    for (int col = 0; col != nframes; col++) {
        for (int row = 0; row != natoms; row++)
            maxmatrixOut.Printf("%g ", MAX.element(col, row));
        maxmatrixOut.Printf("\n");
    }
    maxmatrixOut.CloseFile();
# endif

    return Analysis::OK;
}
예제 #12
0
// Cluster_DBSCAN::ComputeKdistMap()
void Cluster_DBSCAN::ComputeKdistMap( Range const& Kvals, 
                                      std::vector<int> const& FramesToCluster ) const
{
  int pt1_idx, pt2_idx, d_idx, point;
  mprintf("\tCalculating Kdist map for %s\n", Kvals.RangeArg());
  double* kdist_array; // Store distance of pt1 to every other point.
  int nframes = (int)FramesToCluster.size();
  // Ensure all Kdist points are within proper range
  Range::const_iterator kval;
  for (kval = Kvals.begin(); kval != Kvals.end(); ++kval)
    if (*kval < 1 || *kval >= nframes) {
      mprinterr("Error: Kdist value %i is out of range (1 <= Kdist < %i)\n",
                 *kval, nframes);
      return;
    }
  int nvals = (int)Kvals.Size();
  double** KMAP; // KMAP[i] has the ith nearest point for each point.
  KMAP = new double*[ nvals ];
  for (int i = 0; i != nvals; i++)
    KMAP[i] = new double[ nframes ];
  ParallelProgress progress( nframes );
# ifdef _OPENMP
# pragma omp parallel private(pt1_idx, pt2_idx, d_idx, kval, point, kdist_array) firstprivate(progress)
  {
  progress.SetThread( omp_get_thread_num() );
#endif
  kdist_array = new double[ nframes ];
# ifdef _OPENMP
# pragma omp for
# endif
  for (pt1_idx = 0; pt1_idx < nframes; pt1_idx++) // X
  {
    progress.Update( pt1_idx );
    point = FramesToCluster[pt1_idx];
    d_idx = 0;
    // Store distances from pt1 to pt2
    for (pt2_idx = 0; pt2_idx != nframes; pt2_idx++)
      kdist_array[d_idx++] = FrameDistances_.GetFdist(point, FramesToCluster[pt2_idx]);
    // Sort distances; will be smallest to largest
    std::sort( kdist_array, kdist_array + nframes );
    // Save the distance of specified nearest neighbors to this point.
    d_idx = 0;
    for (kval = Kvals.begin(); kval != Kvals.end(); ++kval) // Y
      KMAP[d_idx++][pt1_idx] = kdist_array[ *kval ];
  }
  delete[] kdist_array;
# ifdef _OPENMP
  } // END omp parallel
# endif
  progress.Finish();
  // Sort all of the individual kdist plots, smallest to largest.
  for (int i = 0; i != nvals; i++)
    std::sort(KMAP[i], KMAP[i] + nframes);
  // Save in matrix, largest to smallest.
  DataSet_MatrixDbl kmatrix;
  kmatrix.Allocate2D( FramesToCluster.size(), Kvals.Size() );
  for (int y = 0; y != nvals; y++) {
    for (int x = nframes - 1; x != -1; x--)
      kmatrix.AddElement( KMAP[y][x] );
    delete[] KMAP[y];
  }
  delete[] KMAP;
  // Write matrix to file
  DataFile outfile;
  ArgList outargs("usemap");
  outfile.SetupDatafile(k_prefix_ + "Kmatrix.gnu", outargs, debug_);
  outfile.AddDataSet( (DataSet*)&kmatrix );
  outfile.WriteDataOut();
  // Write out the largest and smallest values for each K.
  // This means for each value of K the point with the furthest Kth-nearest
  // neighbor etc.
  CpptrajFile maxfile;
  if (maxfile.OpenWrite(k_prefix_ + "Kmatrix.max.dat")) return;
  maxfile.Printf("%-12s %12s %12s\n", "#Kval", "MaxD", "MinD");
  d_idx = 0;
  for (kval = Kvals.begin(); kval != Kvals.end(); ++kval, d_idx++)
    maxfile.Printf("%12i %12g %12g\n", *kval, kmatrix.GetElement(0, d_idx),
                   kmatrix.GetElement(nframes-1, d_idx));
  maxfile.CloseFile();
}