Fixed make_edi.c

[gromacs/rigid-bodies.git] / src / tools / gmx_cluster.c

/*
 * 
 *                This source code is part of
 * 
 *                 G   R   O   M   A   C   S
 * 
 *          GROningen MAchine for Chemical Simulations
 * 
 *                        VERSION 3.2.0
 * Written by David van der Spoel, Erik Lindahl, Berk Hess, and others.
 * Copyright (c) 1991-2000, University of Groningen, The Netherlands.
 * Copyright (c) 2001-2004, The GROMACS development team,
 * check out http://www.gromacs.org for more information.

 * This program is free software; you can redistribute it and/or
 * modify it under the terms of the GNU General Public License
 * as published by the Free Software Foundation; either version 2
 * of the License, or (at your option) any later version.
 * 
 * If you want to redistribute modifications, please consider that
 * scientific software is very special. Version control is crucial -
 * bugs must be traceable. We will be happy to consider code for
 * inclusion in the official distribution, but derived work must not
 * be called official GROMACS. Details are found in the README & COPYING
 * files - if they are missing, get the official version at www.gromacs.org.
 * 
 * To help us fund GROMACS development, we humbly ask that you cite
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 * 
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 * And Hey:
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 */
#ifdef HAVE_CONFIG_H
#include <config.h>
#endif
#include <math.h>
#include <string.h>
#include <ctype.h>
#include "macros.h"
#include "smalloc.h"
#include "typedefs.h"
#include "copyrite.h"
#include "statutil.h"
#include "tpxio.h"
#include "string2.h"
#include "vec.h"
#include "macros.h"
#include "index.h"
#include "random.h"
#include "pbc.h"
#include "xvgr.h"
#include "futil.h"
#include "matio.h"
#include "eigensolver.h"
#include "cmat.h"
#include "do_fit.h"
#include "trnio.h"
#include "viewit.h"
#include "gmx_ana.h"

/* macro's to print to two file pointers at once (i.e. stderr and log) */
#define lo_ffprintf(fp1,fp2,buf) \
   fprintf(fp1,"%s",buf);\
   fprintf(fp2,"%s",buf);
/* just print a prepared buffer to fp1 and fp2 */
#define ffprintf(fp1,fp2,buf) { lo_ffprintf(fp1,fp2,buf) }
/* prepare buffer with one argument, then print to fp1 and fp2 */
#define ffprintf1(fp1,fp2,buf,fmt,arg) {\
   sprintf(buf,fmt,arg);\
   lo_ffprintf(fp1,fp2,buf)\
}
/* prepare buffer with two arguments, then print to fp1 and fp2 */
#define ffprintf2(fp1,fp2,buf,fmt,arg1,arg2) {\
   sprintf(buf,fmt,arg1,arg2);\
   lo_ffprintf(fp1,fp2,buf)\
}

typedef struct {
  int ncl;
  int *cl;
} t_clusters;

typedef struct {
  int nr;
  int *nb;
} t_nnb;
  
void pr_energy(FILE *fp,real e)
{
  fprintf(fp,"Energy: %8.4f\n",e);  
}

void cp_index(int nn,int from[],int to[])
{
  int i;
  
  for(i=0; (i<nn); i++)
    to[i]=from[i];
}

void mc_optimize(FILE *log,t_mat *m,int maxiter,int *seed,real kT)
{
  real e[2],ei,ej,efac;
  int  *low_index;
  int  cur=0;
#define next (1-cur)
  int  i,isw,jsw,iisw,jjsw,nn;
  
  fprintf(stderr,"\nDoing Monte Carlo clustering\n");
  nn = m->nn;
  snew(low_index,nn);
  cp_index(nn,m->m_ind,low_index);
  if (getenv("TESTMC")) {
    e[cur] = mat_energy(m);
    pr_energy(log,e[cur]);
    fprintf(log,"Doing 1000 random swaps\n");
    for(i=0; (i<1000); i++) {
      do {
        isw = nn*rando(seed);
        jsw = nn*rando(seed);
      } while ((isw == jsw) || (isw >= nn) || (jsw >= nn));
      iisw = m->m_ind[isw];
      jjsw = m->m_ind[jsw];
      m->m_ind[isw] = jjsw;
      m->m_ind[jsw] = iisw;
    }
  }
  e[cur] = mat_energy(m);
  pr_energy(log,e[cur]);
  for(i=0; (i<maxiter); i++) {
    do {
      isw = nn*rando(seed);
      jsw = nn*rando(seed);
    } while ((isw == jsw) || (isw >= nn) || (jsw >= nn));
    
    iisw = m->m_ind[isw];
    jjsw = m->m_ind[jsw];
    ei   = row_energy(nn,iisw,m->mat[jsw]);
    ej   = row_energy(nn,jjsw,m->mat[isw]);
    
    e[next] = e[cur] + (ei+ej-EROW(m,isw)-EROW(m,jsw))/nn;

    efac = kT ? exp((e[next]-e[cur])/kT) : -1;
    if ((e[next] > e[cur]) || (efac > rando(seed))) {
      
      if (e[next] > e[cur])
        cp_index(nn,m->m_ind,low_index);
      else
        fprintf(log,"Taking uphill step\n");
        
      /* Now swapping rows */
      m->m_ind[isw] = jjsw;
      m->m_ind[jsw] = iisw;
      EROW(m,isw)   = ei;
      EROW(m,jsw)   = ej;
      cur           = next;
      fprintf(log,"Iter: %d Swapped %4d and %4d (now %g)",
              i,isw,jsw,mat_energy(m));
      pr_energy(log,e[cur]);
    }
  }
  /* Now restore the highest energy index */
  cp_index(nn,low_index,m->m_ind);
}

static void calc_dist(int nind,rvec x[],real **d)
{
  int     i,j;
  real    *xi;
  rvec    dx;

  for(i=0; (i<nind-1); i++) {
    xi=x[i];
    for(j=i+1; (j<nind); j++) {
      /* Should use pbc_dx when analysing multiple molecueles,
       * but the box is not stored for every frame.
       */
      rvec_sub(xi,x[j],dx);
      d[i][j]=norm(dx);
    }
  }
}

static real rms_dist(int isize,real **d,real **d_r)
{
  int  i,j;
  real r,r2;
  
  r2=0.0;
  for(i=0; (i<isize-1); i++)
    for(j=i+1; (j<isize); j++) {
      r=d[i][j]-d_r[i][j];
      r2+=r*r;
    }    
  r2/=(isize*(isize-1))/2;
  
  return sqrt(r2);
}

static int rms_dist_comp(const void *a,const void *b)
{
  t_dist *da,*db;
  
  da = (t_dist *)a;
  db = (t_dist *)b;
  
  if (da->dist - db->dist < 0)
    return -1;
  else if (da->dist - db->dist > 0)
    return 1;
  return 0;
}

static int clust_id_comp(const void *a,const void *b)
{
  t_clustid *da,*db;
  
  da = (t_clustid *)a;
  db = (t_clustid *)b;
  
  return da->clust - db->clust;
}

static int nrnb_comp(const void *a, const void *b)
{
  t_nnb *da, *db;
  
  da = (t_nnb *)a;
  db = (t_nnb *)b;
  
  /* return the b-a, we want highest first */
  return db->nr - da->nr;
}

void gather(t_mat *m,real cutoff,t_clusters *clust)
{
  t_clustid *c;
  t_dist    *d;
  int       i,j,k,nn,cid,n1,diff;
  bool      bChange;
  
  /* First we sort the entries in the RMSD matrix */
  n1 = m->nn;
  nn = ((n1-1)*n1)/2;
  snew(d,nn);
  for(i=k=0; (i<n1); i++)
    for(j=i+1; (j<n1); j++,k++) {
      d[k].i    = i;
      d[k].j    = j;
      d[k].dist = m->mat[i][j];
    }
  if (k != nn)
    gmx_incons("gather algortihm");
  qsort(d,nn,sizeof(d[0]),rms_dist_comp);
  
  /* Now we make a cluster index for all of the conformations */
  c = new_clustid(n1);
    
  /* Now we check the closest structures, and equalize their cluster numbers */
  fprintf(stderr,"Linking structures ");
  do {
    fprintf(stderr,"*");
    bChange=FALSE;
    for(k=0; (k<nn) && (d[k].dist < cutoff); k++) {
      diff = c[d[k].j].clust - c[d[k].i].clust;
      if (diff) {
        bChange = TRUE;
        if (diff > 0)
          c[d[k].j].clust = c[d[k].i].clust;
        else
          c[d[k].i].clust = c[d[k].j].clust;
      }
    }
  } while (bChange);
  fprintf(stderr,"\nSorting and renumbering clusters\n");
  /* Sort on cluster number */
  qsort(c,n1,sizeof(c[0]),clust_id_comp);

  /* Renumber clusters */
  cid = 1;
  for(k=1; k<n1; k++) {
    if (c[k].clust != c[k-1].clust) {
      c[k-1].clust = cid;
      cid ++;
    } else
      c[k-1].clust = cid;
  }
  c[k-1].clust = cid;
  if (debug)
    for(k=0; (k<n1); k++)
      fprintf(debug,"Cluster index for conformation %d: %d\n",
              c[k].conf,c[k].clust);
  clust->ncl = cid;
  for(k=0; k<n1; k++)
    clust->cl[c[k].conf] = c[k].clust;

  sfree(c);
  sfree(d);
}

bool jp_same(int **nnb,int i,int j,int P)
{
  bool bIn;
  int  k,ii,jj,pp;

  bIn = FALSE;
  for(k=0; nnb[i][k]>=0; k++)
    bIn = bIn || (nnb[i][k] == j);
  if (!bIn)
    return FALSE;

  bIn = FALSE;
  for(k=0; nnb[j][k]>=0; k++)
    bIn = bIn || (nnb[j][k] == i);
  if (!bIn)
    return FALSE;

  pp=0;
  for(ii=0; nnb[i][ii]>=0; ii++)
    for(jj=0; nnb[j][jj]>=0; jj++)
      if ((nnb[i][ii] == nnb[j][jj]) && (nnb[i][ii] != -1))
        pp++;

  return (pp >= P);
}

static void jarvis_patrick(int n1,real **mat,int M,int P,
                           real rmsdcut,t_clusters *clust)
{
  t_dist    *row;
  t_clustid *c;
  int       **nnb;
  int       i,j,k,cid,diff,max;
  bool      bChange;
  real      **mcpy=NULL;

  if (rmsdcut < 0)
    rmsdcut = 10000;

  /* First we sort the entries in the RMSD matrix row by row.
   * This gives us the nearest neighbor list.
   */
  snew(nnb,n1);
  snew(row,n1);
  for(i=0; (i<n1); i++) {
    for(j=0; (j<n1); j++) {
      row[j].j    = j;
      row[j].dist = mat[i][j];
    }
    qsort(row,n1,sizeof(row[0]),rms_dist_comp);
    if (M>0) {
      /* Put the M nearest neighbors in the list */
      snew(nnb[i],M+1);
      for(j=k=0; (k<M) && (j<n1) && (mat[i][row[j].j] < rmsdcut); j++)
        if (row[j].j  != i) {
          nnb[i][k]  = row[j].j;
          k++;
        }
      nnb[i][k] = -1;
    } else {
      /* Put all neighbors nearer than rmsdcut in the list */
      max=0;
      k=0;
      for(j=0; (j<n1) && (mat[i][row[j].j] < rmsdcut); j++)
        if (row[j].j != i) {
          if (k >= max) {
            max += 10;
            srenew(nnb[i],max);
          }
          nnb[i][k] = row[j].j;
          k++;
        }
      if (k == max)
        srenew(nnb[i],max+1);
      nnb[i][k] = -1;
    }
  }
  sfree(row);
  if (debug) {
    fprintf(debug,"Nearest neighborlist. M = %d, P = %d\n",M,P);
    for(i=0; (i<n1); i++) {
      fprintf(debug,"i:%5d nbs:",i);
      for(j=0; nnb[i][j]>=0; j++)
        fprintf(debug,"%5d[%5.3f]",nnb[i][j],mat[i][nnb[i][j]]);
      fprintf(debug,"\n");
    }
  }

  c = new_clustid(n1);
  fprintf(stderr,"Linking structures ");
  /* Use mcpy for temporary storage of booleans */
  mcpy = mk_matrix(n1,n1,FALSE);
  for(i=0; i<n1; i++)
    for(j=i+1; j<n1; j++)
      mcpy[i][j] = jp_same(nnb,i,j,P);
  do {
    fprintf(stderr,"*");
    bChange=FALSE;
    for(i=0; i<n1; i++) {
      for(j=i+1; j<n1; j++)
        if (mcpy[i][j]) {
          diff = c[j].clust - c[i].clust;
          if (diff) {
            bChange = TRUE;
            if (diff > 0)
              c[j].clust = c[i].clust;
            else
              c[i].clust = c[j].clust;
          }
        }
    }
  } while (bChange);
  
  fprintf(stderr,"\nSorting and renumbering clusters\n");
  /* Sort on cluster number */
  qsort(c,n1,sizeof(c[0]),clust_id_comp);

  /* Renumber clusters */
  cid = 1;
  for(k=1; k<n1; k++) {
    if (c[k].clust != c[k-1].clust) {
      c[k-1].clust = cid;
      cid ++;
    } else
      c[k-1].clust = cid;
  }
  c[k-1].clust = cid;
  clust->ncl = cid;
  for(k=0; k<n1; k++)
    clust->cl[c[k].conf] = c[k].clust;
  if (debug)
    for(k=0; (k<n1); k++)
      fprintf(debug,"Cluster index for conformation %d: %d\n",
              c[k].conf,c[k].clust);

/* Again, I don't see the point in this... (AF) */
/*   for(i=0; (i<n1); i++) { */
/*     for(j=0; (j<n1); j++) */
/*       mcpy[c[i].conf][c[j].conf] = mat[i][j]; */
/*   } */
/*   for(i=0; (i<n1); i++) { */
/*     for(j=0; (j<n1); j++) */
/*       mat[i][j] = mcpy[i][j]; */
/*   } */
  done_matrix(n1,&mcpy);
  
  sfree(c);
  for(i=0; (i<n1); i++)
    sfree(nnb[i]);
  sfree(nnb);
}

static void dump_nnb (FILE *fp, const char *title, int n1, t_nnb *nnb)
{
  int i,j;
  
  /* dump neighbor list */
  fprintf(fp,"%s",title);
  for(i=0; (i<n1); i++) {
    fprintf(fp,"i:%5d #:%5d nbs:",i,nnb[i].nr);
    for(j=0; j<nnb[i].nr; j++)
      fprintf(fp,"%5d",nnb[i].nb[j]);
    fprintf(fp,"\n");
  }
}
  
static void gromos(int n1, real **mat, real rmsdcut, t_clusters *clust)
{
  t_dist *row;
  t_nnb  *nnb;
  int    i,j,k,j1,max;

  /* Put all neighbors nearer than rmsdcut in the list */
  fprintf(stderr,"Making list of neighbors within cutoff ");
  snew(nnb,n1);
  snew(row,n1);
  for(i=0; (i<n1); i++) {
    max=0;
    k=0;
    /* put all neighbors within cut-off in list */
    for(j=0; j<n1; j++) 
      if (mat[i][j] < rmsdcut) {
        if (k >= max) {
          max += 10;
          srenew(nnb[i].nb,max);
        }
        nnb[i].nb[k] = j;
        k++;
      }
    /* store nr of neighbors, we'll need that */
    nnb[i].nr = k;
    if (i%(1+n1/100)==0) fprintf(stderr,"%3d%%\b\b\b\b",(i*100+1)/n1);
  }
  fprintf(stderr,"%3d%%\n",100);
  sfree(row);
  
  /* sort neighbor list on number of neighbors, largest first */
  qsort(nnb,n1,sizeof(nnb[0]),nrnb_comp);

  if (debug) dump_nnb(debug, "Nearest neighborlist after sort.\n", n1, nnb);
  
  /* turn first structure with all its neighbors (largest) into cluster
     remove them from pool of structures and repeat for all remaining */
  fprintf(stderr,"Finding clusters %4d", 0);
  /* cluster id's start at 1: */
  k=1;
  while(nnb[0].nr) {
    /* set cluster id (k) for first item in neighborlist */
    for (j=0; j<nnb[0].nr; j++)
      clust->cl[nnb[0].nb[j]] = k;
    /* mark as done */
    nnb[0].nr=0;
    sfree(nnb[0].nb);
    
    /* adjust number of neighbors for others, taking removals into account: */
    for(i=1; i<n1 && nnb[i].nr; i++) {
      j1=0;
      for(j=0; j<nnb[i].nr; j++)
        /* if this neighbor wasn't removed */
        if ( clust->cl[nnb[i].nb[j]] == 0 ) {
          /* shift the rest (j1<=j) */
          nnb[i].nb[j1]=nnb[i].nb[j];
          /* next */
          j1++;
        }
      /* now j1 is the new number of neighbors */
      nnb[i].nr=j1;
    }
    /* sort again on nnb[].nr, because we have new # neighbors: */
    /* but we only need to sort upto i, i.e. when nnb[].nr>0 */
    qsort(nnb,i,sizeof(nnb[0]),nrnb_comp);
    
    fprintf(stderr,"\b\b\b\b%4d",k);
    /* new cluster id */
    k++;
  }
  fprintf(stderr,"\n");
  sfree(nnb);
  if (debug) {
    fprintf(debug,"Clusters (%d):\n", k);
    for(i=0; i<n1; i++)
      fprintf(debug," %3d", clust->cl[i]);
    fprintf(debug,"\n");
  }

  clust->ncl=k-1;
}

rvec **read_whole_trj(const char *fn,int isize,atom_id index[],int skip,
                      int *nframe, real **time,const output_env_t oenv)
{
  rvec   **xx,*x;
  matrix box;
  real   t;
  int    i,i0,j,max_nf;
  int    status,natom;
  
  max_nf = 0;
  xx     = NULL;
  *time  = NULL;
  natom = read_first_x(oenv,&status,fn,&t,&x,box);
  i  = 0;
  i0 = 0;
  do {
    if (i0 >= max_nf) {
      max_nf += 10;
      srenew(xx,max_nf);
      srenew(*time,max_nf);
    }
    if ((i % skip) == 0) {
      snew(xx[i0],isize);
      /* Store only the interesting atoms */
      for(j=0; (j<isize); j++) 
        copy_rvec(x[index[j]],xx[i0][j]);
      (*time)[i0] = t;
      i0 ++;
    }
    i++;
  } while (read_next_x(oenv,status,&t,natom,x,box));
  fprintf(stderr,"Allocated %lu bytes for frames\n",
          (unsigned long) (max_nf*isize*sizeof(**xx)));
  fprintf(stderr,"Read %d frames from trajectory %s\n",i0,fn);
  *nframe = i0;
  sfree(x);
  
  return xx;
}

static int plot_clusters(int nf, real **mat, t_clusters *clust,
                         int nlevels, int minstruct)
{
  int i,j,ncluster,ci;
  int *cl_id,*nstruct,*strind;
    
  snew(cl_id,nf);
  snew(nstruct,nf);
  snew(strind,nf);
  for(i=0; i<nf; i++) {
    strind[i] = 0;
    cl_id[i]  = clust->cl[i];
    nstruct[cl_id[i]]++;
  }
  ncluster = 0;
  for(i=0; i<nf; i++) {
    if (nstruct[i] >= minstruct) {
      ncluster++;
      for(j=0; (j<nf); j++)
        if (cl_id[j] == i)
          strind[j] = ncluster;
    }
  }
  ncluster++;
  fprintf(stderr,"There are %d clusters with at least %d conformations\n",
            ncluster,minstruct);
  
  for(i=0; (i<nf); i++) {
    ci = cl_id[i];
    for(j=0; j<i; j++)
      if ((ci == cl_id[j]) && (nstruct[ci] >= minstruct)) {
        /* color different clusters with different colors, as long as
           we don't run out of colors */
        mat[i][j] = strind[i];
      } 
      else
        mat[i][j] = 0;
  }
  sfree(strind);
  sfree(nstruct);
  sfree(cl_id);

  return ncluster;
}

static void mark_clusters(int nf, real **mat, real val, t_clusters *clust)
{
  int i,j,v;
  
  for(i=0; i<nf; i++)
    for(j=0; j<i; j++)
      if (clust->cl[i] == clust->cl[j])
        mat[i][j] = val;
      else
        mat[i][j] = 0;
}

static char *parse_filename(const char *fn, int maxnr)
{
  int i;
  char *fnout;
  const char *ext;
  char buf[STRLEN];
  
  if (strchr(fn,'%'))
    gmx_fatal(FARGS,"will not number filename %s containing '%c'",fn,'%');
  /* number of digits needed in numbering */
  i = (int)(log(maxnr)/log(10)) + 1;
  /* split fn and ext */
  ext = strrchr(fn, '.');
  if (!ext)
    gmx_fatal(FARGS,"cannot separate extension in filename %s",fn);
  ext++;
  /* insert e.g. '%03d' between fn and ext */
  sprintf(buf,"%s%%0%dd.%s",fn,i,ext);
  snew(fnout,strlen(buf)+1);
  strcpy(fnout, buf);
  
  return fnout;
}

static void ana_trans(t_clusters *clust, int nf, 
                      const char *transfn, const char *ntransfn, FILE *log,
                      t_rgb rlo,t_rgb rhi,const output_env_t oenv)
{
  FILE *fp;
  real **trans,*axis;
  int  *ntrans;
  int  i,ntranst,maxtrans;
  char buf[STRLEN];
  
  snew(ntrans,clust->ncl);
  snew(trans,clust->ncl);
  snew(axis,clust->ncl);
  for(i=0; i<clust->ncl; i++) {
    axis[i]=i+1;
    snew(trans[i],clust->ncl);
  }
  ntranst=0;
  maxtrans=0;
  for(i=1; i<nf; i++)
    if(clust->cl[i] != clust->cl[i-1]) {
      ntranst++;
      ntrans[clust->cl[i-1]-1]++;
      ntrans[clust->cl[i]-1]++;
      trans[clust->cl[i-1]-1][clust->cl[i]-1]++;
      maxtrans = max(maxtrans, trans[clust->cl[i]-1][clust->cl[i-1]-1]);
    }
  ffprintf2(stderr,log,buf,"Counted %d transitions in total, "
            "max %d between two specific clusters\n",ntranst,maxtrans);
  if (transfn) {
    fp=ffopen(transfn,"w");
    i = min(maxtrans+1, 80);
    write_xpm(fp,0,"Cluster Transitions","# transitions",
              "from cluster","to cluster", 
              clust->ncl, clust->ncl, axis, axis, trans, 
              0, maxtrans, rlo, rhi, &i);
    ffclose(fp);
  }
  if (ntransfn) {
    fp=xvgropen(ntransfn,"Cluster Transitions","Cluster #","# transitions",
                oenv);
    for(i=0; i<clust->ncl; i++)
      fprintf(fp,"%5d %5d\n",i+1,ntrans[i]);
    ffclose(fp);
  }
  sfree(ntrans);
  for(i=0; i<clust->ncl; i++)
    sfree(trans[i]);
  sfree(trans);
  sfree(axis);
}

static void analyze_clusters(int nf, t_clusters *clust, real **rmsd,
                             int natom, t_atoms *atoms, rvec *xtps, 
                             real *mass, rvec **xx, real *time,
                             int ifsize, atom_id *fitidx,
                             int iosize, atom_id *outidx,
                             const char *trxfn, const char *sizefn, 
                             const char *transfn, const char *ntransfn, 
                             const char *clustidfn, bool bAverage, 
                             int write_ncl, int write_nst, real rmsmin,
                             bool bFit, FILE *log,t_rgb rlo,t_rgb rhi,
                             const output_env_t oenv)
{
  FILE *fp=NULL;
  char buf[STRLEN],buf1[40],buf2[40],buf3[40],*trxsfn;
  int  trxout=0,trxsout=0;
  int  i,i1,cl,nstr,*structure,first=0,midstr;
  bool *bWrite=NULL;
  real r,clrmsd,midrmsd;
  rvec *xav=NULL;
  matrix zerobox;
  
  clear_mat(zerobox);
  
  ffprintf1(stderr,log,buf,"\nFound %d clusters\n\n",clust->ncl);
  trxsfn=NULL;
  if (trxfn) {
    /* do we write all structures? */
    if (write_ncl) {
      trxsfn = parse_filename(trxfn, max(write_ncl,clust->ncl));
      snew(bWrite,nf);
    }
    ffprintf2(stderr,log,buf,"Writing %s structure for each cluster to %s\n",
              bAverage ? "average" : "middle", trxfn);
    if (write_ncl) {
      /* find out what we want to tell the user:
         Writing [all structures|structures with rmsd > %g] for 
         {all|first %d} clusters {with more than %d structures} to %s     */
      if (rmsmin>0.0)
        sprintf(buf1,"structures with rmsd > %g",rmsmin);
      else
        sprintf(buf1,"all structures");
      buf2[0]=buf3[0]='\0';
      if (write_ncl>=clust->ncl) {
        if (write_nst==0)
          sprintf(buf2,"all ");
      } else
        sprintf(buf2,"the first %d ",write_ncl);
      if (write_nst)
        sprintf(buf3," with more than %d structures",write_nst);
      sprintf(buf,"Writing %s for %sclusters%s to %s\n",buf1,buf2,buf3,trxsfn);
      ffprintf(stderr,log,buf);
    }
  
    /* Prepare a reference structure for the orientation of the clusters  */
    if (bFit)
    reset_x(ifsize,fitidx,natom,NULL,xtps,mass);
    trxout = open_trx(trxfn,"w");
    /* Calculate the average structure in each cluster,               *
     * all structures are fitted to the first struture of the cluster */
    snew(xav,natom);
  }
  
  if (transfn || ntransfn) 
    ana_trans(clust, nf, transfn, ntransfn, log,rlo,rhi,oenv);
  
  if (clustidfn) {
    fp=xvgropen(clustidfn,"Clusters",output_env_get_xvgr_tlabel(oenv),"Cluster #",oenv);
    fprintf(fp,"@    s0 symbol 2\n");
    fprintf(fp,"@    s0 symbol size 0.2\n");
    fprintf(fp,"@    s0 linestyle 0\n");
    for(i=0; i<nf; i++)
      fprintf(fp,"%8g %8d\n",time[i],clust->cl[i]);
    ffclose(fp);
  }
  if (sizefn) {
    fp=xvgropen(sizefn,"Cluster Sizes","Cluster #","# Structures",oenv);
    fprintf(fp,"@g%d type %s\n",0,"bar");
  }
  snew(structure,nf);
  fprintf(log,"\n%3s | %3s  %4s | %6s %4s | cluster members\n",
          "cl.","#st","rmsd","middle","rmsd");
  for(cl=1; cl<=clust->ncl; cl++) {
    /* prepare structures (fit, middle, average) */
    if (xav)
      for(i=0; i<natom;i++)
        clear_rvec(xav[i]);
    nstr=0;
    for(i1=0; i1<nf; i1++)
      if (clust->cl[i1] == cl) {
        structure[nstr] = i1;
        nstr++;
        if (trxfn && (bAverage || write_ncl) ) {
          if (bFit)
          reset_x(ifsize,fitidx,natom,NULL,xx[i1],mass);
          if (nstr == 1)
            first = i1;
          else if (bFit)
            do_fit(natom,mass,xx[first],xx[i1]);
          if (xav)
            for(i=0; i<natom; i++)
              rvec_inc(xav[i],xx[i1][i]);
        }
      }
    if (sizefn)
      fprintf(fp,"%8d %8d\n",cl,nstr);
    clrmsd = 0;
    midstr = 0;
    midrmsd = 10000;
    for(i1=0; i1<nstr; i1++) {
      r = 0;
      if (nstr > 1) {
        for(i=0; i<nstr; i++)
          if (i < i1)
            r += rmsd[structure[i]][structure[i1]];
          else
            r += rmsd[structure[i1]][structure[i]];
        r /= (nstr - 1);
      }
      if ( r < midrmsd ) {
        midstr = structure[i1];
        midrmsd = r;
      }
      clrmsd += r;
    }
    clrmsd /= nstr;
    
    /* dump cluster info to logfile */
    if (nstr > 1) {
      sprintf(buf1,"%6.3f",clrmsd);
      if (buf1[0] == '0')
        buf1[0] = ' ';
      sprintf(buf2,"%5.3f",midrmsd);
      if (buf2[0] == '0')
        buf2[0] = ' ';
    } else {
      sprintf(buf1,"%5s","");
      sprintf(buf2,"%5s","");
    }
    fprintf(log,"%3d | %3d %s | %6g%s |",cl,nstr,buf1,time[midstr],buf2);
    for(i=0; i<nstr; i++) {
      if ((i % 7 == 0) && i)
        sprintf(buf,"\n%3s | %3s  %4s | %6s %4s |","","","","","");
      else
        buf[0] = '\0';
      i1 = structure[i];
      fprintf(log,"%s %6g",buf,time[i1]);
    }
    fprintf(log,"\n");
    
    /* write structures to trajectory file(s) */
    if (trxfn) {
      if (write_ncl)
        for(i=0; i<nstr; i++)
          bWrite[i]=FALSE;
      if ( cl < write_ncl+1 && nstr > write_nst ) {
        /* Dump all structures for this cluster */
        /* generate numbered filename (there is a %d in trxfn!) */
        sprintf(buf,trxsfn,cl);
        trxsout = open_trx(buf,"w");
        for(i=0; i<nstr; i++) {
          bWrite[i] = TRUE;
          if (rmsmin>0.0)
            for(i1=0; i1<i && bWrite[i]; i1++)
              if (bWrite[i1])
                bWrite[i] = rmsd[structure[i1]][structure[i]] > rmsmin;
          if (bWrite[i])
            write_trx(trxsout,iosize,outidx,atoms,i,time[structure[i]],zerobox,
                      xx[structure[i]],NULL,NULL);
        }
        close_trx(trxsout);
      } 
      /* Dump the average structure for this cluster */
      if (bAverage) {
        for(i=0; i<natom; i++)
          svmul(1.0/nstr,xav[i],xav[i]);
      } else {
        for(i=0; i<natom; i++)
          copy_rvec(xx[midstr][i],xav[i]);
        if (bFit)
        reset_x(ifsize,fitidx,natom,NULL,xav,mass);
      }
      if (bFit)
        do_fit(natom,mass,xtps,xav);
      r = cl;
      write_trx(trxout,iosize,outidx,atoms,cl,time[midstr],zerobox,xav,NULL,NULL);
    }
  }
  /* clean up */
  if (trxfn) {
    close_trx(trxout);
    sfree(xav);
    if (write_ncl)
      sfree(bWrite);
  }
  sfree(structure);
  if (trxsfn)
    sfree(trxsfn);
}

static void convert_mat(t_matrix *mat,t_mat *rms)
{
  int i,j;

  rms->n1 = mat->nx;
  matrix2real(mat,rms->mat);
  /* free input xpm matrix data */
  for(i=0; i<mat->nx; i++)
    sfree(mat->matrix[i]);
  sfree(mat->matrix);
  
  for(i=0; i<mat->nx; i++)
    for(j=i; j<mat->nx; j++) {
      rms->sumrms += rms->mat[i][j];
      rms->maxrms = max(rms->maxrms, rms->mat[i][j]);
      if (j!=i)
        rms->minrms = min(rms->minrms, rms->mat[i][j]);
    }
  rms->nn = mat->nx;
}  

int gmx_cluster(int argc,char *argv[])
{
  const char *desc[] = {
    "g_cluster can cluster structures with several different methods.",
    "Distances between structures can be determined from a trajectory",
    "or read from an XPM matrix file with the [TT]-dm[tt] option.",
    "RMS deviation after fitting or RMS deviation of atom-pair distances",
    "can be used to define the distance between structures.[PAR]",
    
    "single linkage: add a structure to a cluster when its distance to any",
    "element of the cluster is less than [TT]cutoff[tt].[PAR]",
    
    "Jarvis Patrick: add a structure to a cluster when this structure",
    "and a structure in the cluster have each other as neighbors and",
    "they have a least [TT]P[tt] neighbors in common. The neighbors",
    "of a structure are the M closest structures or all structures within",
    "[TT]cutoff[tt].[PAR]",
    
    "Monte Carlo: reorder the RMSD matrix using Monte Carlo.[PAR]",
    
    "diagonalization: diagonalize the RMSD matrix.[PAR]",
    
    "gromos: use algorithm as described in Daura [IT]et al.[it]",
    "([IT]Angew. Chem. Int. Ed.[it] [BB]1999[bb], [IT]38[it], pp 236-240).",
    "Count number of neighbors using cut-off, take structure with",
    "largest number of neighbors with all its neighbors as cluster",
    "and eleminate it from the pool of clusters. Repeat for remaining",
    "structures in pool.[PAR]",
    
    "When the clustering algorithm assigns each structure to exactly one",
    "cluster (single linkage, Jarvis Patrick and gromos) and a trajectory",
    "file is supplied, the structure with",
    "the smallest average distance to the others or the average structure",
    "or all structures for each cluster will be written to a trajectory",
    "file. When writing all structures, separate numbered files are made",
    "for each cluster.[PAR]",
    
    "Two output files are always written:[BR]",
    "[TT]-o[tt] writes the RMSD values in the upper left half of the matrix",
    "and a graphical depiction of the clusters in the lower right half",
    "When [TT]-minstruct[tt] = 1 the graphical depiction is black",
    "when two structures are in the same cluster.",
    "When [TT]-minstruct[tt] > 1 different colors will be used for each",
    "cluster.[BR]",
    "[TT]-g[tt] writes information on the options used and a detailed list",
    "of all clusters and their members.[PAR]",
    
    "Additionally, a number of optional output files can be written:[BR]",
    "[TT]-dist[tt] writes the RMSD distribution.[BR]",
    "[TT]-ev[tt] writes the eigenvectors of the RMSD matrix",
    "diagonalization.[BR]",
    "[TT]-sz[tt] writes the cluster sizes.[BR]",
    "[TT]-tr[tt] writes a matrix of the number transitions between",
    "cluster pairs.[BR]",
    "[TT]-ntr[tt] writes the total number of transitions to or from",
    "each cluster.[BR]",
    "[TT]-clid[tt] writes the cluster number as a function of time.[BR]",
    "[TT]-cl[tt] writes average (with option [TT]-av[tt]) or central",
    "structure of each cluster or writes numbered files with cluster members",
    "for a selected set of clusters (with option [TT]-wcl[tt], depends on",
    "[TT]-nst[tt] and [TT]-rmsmin[tt]).[BR]",
  };
  
  FILE         *fp,*log;
  int          i,i1,i2,j,nf,nrms;

  matrix       box;
  rvec         *xtps,*usextps,*x1,**xx=NULL;
  const char   *fn,*trx_out_fn;
  t_clusters   clust;
  t_mat        *rms;
  real         *eigval;
  t_topology   top;
  int          ePBC;
  t_atoms      useatoms;
  t_matrix     *readmat=NULL;
  real         *tmp;
  
  int      isize=0,ifsize=0,iosize=0;
  atom_id  *index=NULL, *fitidx, *outidx;
  char     *grpname;
  real     rmsd,**d1,**d2,*time=NULL,time_invfac,*mass=NULL;
  char     buf[STRLEN],buf1[80],title[STRLEN];
  bool     bAnalyze,bUseRmsdCut,bJP_RMSD=FALSE,bReadMat,bReadTraj;

  int method,ncluster=0;  
  static const char *methodname[] = { 
    NULL, "linkage", "jarvis-patrick","monte-carlo", 
    "diagonalization", "gromos", NULL
  };
  enum { m_null, m_linkage, m_jarvis_patrick, 
         m_monte_carlo, m_diagonalize, m_gromos, m_nr };
  /* Set colors for plotting: white = zero RMS, black = maximum */
  static t_rgb rlo_top = { 1.0, 1.0, 1.0 };
  static t_rgb rhi_top = { 0.0, 0.0, 0.0 };
  static t_rgb rlo_bot = { 1.0, 1.0, 1.0 };
  static t_rgb rhi_bot = { 0.0, 0.0, 1.0 };
  static int  nlevels=40,skip=1;
  static real scalemax=-1.0,rmsdcut=0.1,rmsmin=0.0;
  static bool bRMSdist=FALSE,bBinary=FALSE,bAverage=FALSE,bFit=TRUE;
  static int  niter=10000,seed=1993,write_ncl=0,write_nst=1,minstruct=1;
  static real kT=1e-3;
  static int  M=10,P=3;
  output_env_t oenv;
  t_pargs pa[] = {
    { "-dista", FALSE, etBOOL, {&bRMSdist},
      "Use RMSD of distances instead of RMS deviation" },
    { "-nlevels",FALSE,etINT,  {&nlevels},
      "Discretize RMSD matrix in # levels" },
    { "-cutoff",FALSE, etREAL, {&rmsdcut},
      "RMSD cut-off (nm) for two structures to be neighbor" },
    { "-fit",   FALSE, etBOOL, {&bFit},
      "Use least squares fitting before RMSD calculation" },
    { "-max",   FALSE, etREAL, {&scalemax},
      "Maximum level in RMSD matrix" },
    { "-skip",  FALSE, etINT,  {&skip},
      "Only analyze every nr-th frame" },
    { "-av",    FALSE, etBOOL, {&bAverage},
      "Write average iso middle structure for each cluster" },
    { "-wcl",   FALSE, etINT,  {&write_ncl},
      "Write all structures for first # clusters to numbered files" },
    { "-nst",   FALSE, etINT,  {&write_nst},
      "Only write all structures if more than # per cluster" },
    { "-rmsmin",FALSE, etREAL, {&rmsmin},
      "minimum rms difference with rest of cluster for writing structures" },
    { "-method",FALSE, etENUM, {methodname},
      "Method for cluster determination" },
    { "-minstruct", FALSE, etINT, {&minstruct},
      "Minimum number of structures in cluster for coloring in the xpm file" },
    { "-binary",FALSE, etBOOL, {&bBinary},
      "Treat the RMSD matrix as consisting of 0 and 1, where the cut-off "
      "is given by -cutoff" },
    { "-M",     FALSE, etINT,  {&M},
      "Number of nearest neighbors considered for Jarvis-Patrick algorithm, "
      "0 is use cutoff" },
    { "-P",     FALSE, etINT,  {&P},
      "Number of identical nearest neighbors required to form a cluster" },
    { "-seed",  FALSE, etINT,  {&seed},
      "Random number seed for Monte Carlo clustering algorithm" },
    { "-niter", FALSE, etINT,  {&niter},
      "Number of iterations for MC" },
    { "-kT",    FALSE, etREAL, {&kT},
      "Boltzmann weighting factor for Monte Carlo optimization "
      "(zero turns off uphill steps)" }
  };
  t_filenm fnm[] = {
    { efTRX, "-f",     NULL,        ffOPTRD },
    { efTPS, "-s",     NULL,        ffOPTRD },
    { efNDX, NULL,     NULL,        ffOPTRD },
    { efXPM, "-dm",   "rmsd",       ffOPTRD },     
    { efXPM, "-o",    "rmsd-clust", ffWRITE },
    { efLOG, "-g",    "cluster",    ffWRITE },
    { efXVG, "-dist", "rmsd-dist",  ffOPTWR },
    { efXVG, "-ev",   "rmsd-eig",   ffOPTWR },
    { efXVG, "-sz",   "clust-size", ffOPTWR},
    { efXPM, "-tr",   "clust-trans",ffOPTWR},
    { efXVG, "-ntr",  "clust-trans",ffOPTWR},
    { efXVG, "-clid", "clust-id.xvg",ffOPTWR},
    { efTRX, "-cl",   "clusters.pdb", ffOPTWR }
  };
#define NFILE asize(fnm)
  
  CopyRight(stderr,argv[0]);
  parse_common_args(&argc,argv,
                    PCA_CAN_VIEW | PCA_CAN_TIME | PCA_TIME_UNIT | PCA_BE_NICE,
                    NFILE,fnm,asize(pa),pa,asize(desc),desc,0,NULL,
                    &oenv);

  /* parse options */
  bReadMat   = opt2bSet("-dm",NFILE,fnm);
  bReadTraj  = opt2bSet("-f",NFILE,fnm) || !bReadMat;
  if ( opt2parg_bSet("-av",asize(pa),pa) ||
       opt2parg_bSet("-wcl",asize(pa),pa) ||
       opt2parg_bSet("-nst",asize(pa),pa) ||
       opt2parg_bSet("-rmsmin",asize(pa),pa) ||
       opt2bSet("-cl",NFILE,fnm) )
    trx_out_fn = opt2fn("-cl",NFILE,fnm);
  else
    trx_out_fn = NULL;
  if (bReadMat && output_env_get_time_factor(oenv)!=1) {
    fprintf(stderr,
            "\nWarning: assuming the time unit in %s is %s\n",
            opt2fn("-dm",NFILE,fnm),output_env_get_time_unit(oenv));
  }
  if (trx_out_fn && !bReadTraj)
    fprintf(stderr,"\nWarning: "
            "cannot write cluster structures without reading trajectory\n"
            "         ignoring option -cl %s\n", trx_out_fn);

  method=1;
  while ( method < m_nr && strcasecmp(methodname[0], methodname[method])!=0 )
    method++;
  if (method == m_nr)
    gmx_fatal(FARGS,"Invalid method");
  
  bAnalyze = (method == m_linkage || method == m_jarvis_patrick ||
              method == m_gromos );
  
  /* Open log file */
  log = ftp2FILE(efLOG,NFILE,fnm,"w");

  fprintf(stderr,"Using %s method for clustering\n",methodname[0]);
  fprintf(log,"Using %s method for clustering\n",methodname[0]);

  /* check input and write parameters to log file */
  bUseRmsdCut = FALSE;
  if (method == m_jarvis_patrick) {
    bJP_RMSD = (M == 0) || opt2parg_bSet("-cutoff",asize(pa),pa);
    if ((M<0) || (M == 1))
      gmx_fatal(FARGS,"M (%d) must be 0 or larger than 1",M);
    if (M < 2) {
      sprintf(buf1,"Will use P=%d and RMSD cutoff (%g)",P,rmsdcut);
      bUseRmsdCut = TRUE;
    } else {
      if (P >= M)
        gmx_fatal(FARGS,"Number of neighbors required (P) must be less than M");
      if (bJP_RMSD) {
        sprintf(buf1,"Will use P=%d, M=%d and RMSD cutoff (%g)",P,M,rmsdcut);
        bUseRmsdCut = TRUE;
      } else
        sprintf(buf1,"Will use P=%d, M=%d",P,M);
    }
    ffprintf1(stderr,log,buf,"%s for determining the neighbors\n\n",buf1);
  } else /* method != m_jarvis */
    bUseRmsdCut = ( bBinary || method == m_linkage || method == m_gromos );
  if (bUseRmsdCut && method != m_jarvis_patrick)
    fprintf(log,"Using RMSD cutoff %g nm\n",rmsdcut);
  if ( method==m_monte_carlo )
    fprintf(log,"Using %d iterations\n",niter);
  
  if (skip < 1)
    gmx_fatal(FARGS,"skip (%d) should be >= 1",skip);

  /* get input */
  if (bReadTraj) {
    /* don't read mass-database as masses (and top) are not used */
    read_tps_conf(ftp2fn(efTPS,NFILE,fnm),buf,&top,&ePBC,&xtps,NULL,box,
                  bAnalyze);
    
    fprintf(stderr,"\nSelect group for least squares fit%s:\n",
            bReadMat?"":" and RMSD calculation");
    get_index(&(top.atoms),ftp2fn_null(efNDX,NFILE,fnm),
              1,&ifsize,&fitidx,&grpname);
    if (trx_out_fn) {
      fprintf(stderr,"\nSelect group for output:\n");
      get_index(&(top.atoms),ftp2fn_null(efNDX,NFILE,fnm),
                1,&iosize,&outidx,&grpname);
      /* merge and convert both index groups: */
      /* first copy outidx to index. let outidx refer to elements in index */
      snew(index,iosize);
      isize = iosize;
      for(i=0; i<iosize; i++) {
        index[i]=outidx[i];
        outidx[i]=i;
      }
      /* now lookup elements from fitidx in index, add them if necessary
         and also let fitidx refer to elements in index */
      for(i=0; i<ifsize; i++) {
        j=0;
        while (j<isize && index[j]!=fitidx[i])
          j++;
        if (j>=isize) {
          /* slow this way, but doesn't matter much */
          isize++;
          srenew(index,isize);
        }
        index[j]=fitidx[i];
        fitidx[i]=j;
      }
    } else { /* !trx_out_fn */
      isize = ifsize;
      snew(index, isize);
      for(i=0; i<ifsize; i++) {
        index[i]=fitidx[i];
        fitidx[i]=i;
      }
    }
  }
  /* Initiate arrays */
  snew(d1,isize);
  snew(d2,isize);
  for(i=0; (i<isize); i++) {
    snew(d1[i],isize);
    snew(d2[i],isize);
  }

  if (bReadTraj) {
    /* Loop over first coordinate file */
    fn = opt2fn("-f",NFILE,fnm);
    
    xx = read_whole_trj(fn,isize,index,skip,&nf,&time,oenv);
    output_env_conv_times(oenv, nf, time);
    if (!bRMSdist || bAnalyze) {
      /* Center all frames on zero */
      snew(mass,isize);
      for(i=0; i<ifsize; i++)
        mass[fitidx[i]] = top.atoms.atom[index[fitidx[i]]].m;
      if (bFit)
      for(i=0; i<nf; i++)
        reset_x(ifsize,fitidx,isize,NULL,xx[i],mass);
    }
  }
  if (bReadMat) {
    fprintf(stderr,"Reading rms distance matrix ");
    read_xpm_matrix(opt2fn("-dm",NFILE,fnm),&readmat);
    fprintf(stderr,"\n");
    if (readmat[0].nx != readmat[0].ny)
      gmx_fatal(FARGS,"Matrix (%dx%d) is not square",
                  readmat[0].nx,readmat[0].ny);
    if (bReadTraj && bAnalyze && (readmat[0].nx != nf))
      gmx_fatal(FARGS,"Matrix size (%dx%d) does not match the number of "
                  "frames (%d)",readmat[0].nx,readmat[0].ny,nf);

    nf = readmat[0].nx;
    sfree(time);
    time = readmat[0].axis_x;
    time_invfac = output_env_get_time_invfactor(oenv);
    for(i=0; i<nf; i++)
      time[i] *= time_invfac;

    rms = init_mat(readmat[0].nx,method == m_diagonalize);
    convert_mat(&(readmat[0]),rms);
    
    nlevels = readmat[0].nmap;
  } else { /* !bReadMat */
    rms = init_mat(nf,method == m_diagonalize);
    nrms = (nf*(nf-1))/2;
    if (!bRMSdist) {
      fprintf(stderr,"Computing %dx%d RMS deviation matrix\n",nf,nf);
      snew(x1,isize);
      for(i1=0; (i1<nf); i1++) {
        for(i2=i1+1; (i2<nf); i2++) {
          for(i=0; i<isize; i++)
            copy_rvec(xx[i1][i],x1[i]);
          if (bFit)
            do_fit(isize,mass,xx[i2],x1);
          rmsd = rmsdev(isize,mass,xx[i2],x1);
          set_mat_entry(rms,i1,i2,rmsd);
        }
        nrms -= (nf-i1-1);
        fprintf(stderr,"\r# RMSD calculations left: %d   ",nrms);
      }
    } else { /* bRMSdist */
      fprintf(stderr,"Computing %dx%d RMS distance deviation matrix\n",nf,nf);
      for(i1=0; (i1<nf); i1++) {
        calc_dist(isize,xx[i1],d1);
        for(i2=i1+1; (i2<nf); i2++) {
          calc_dist(isize,xx[i2],d2);
          set_mat_entry(rms,i1,i2,rms_dist(isize,d1,d2));
      }
        nrms -= (nf-i1-1);
        fprintf(stderr,"\r# RMSD calculations left: %d   ",nrms);
      }
    }
    fprintf(stderr,"\n\n");
  }
  ffprintf2(stderr,log,buf,"The RMSD ranges from %g to %g nm\n",
            rms->minrms,rms->maxrms);
  ffprintf1(stderr,log,buf,"Average RMSD is %g\n",2*rms->sumrms/(nf*(nf-1)));
  ffprintf1(stderr,log,buf,"Number of structures for matrix %d\n",nf);
  ffprintf1(stderr,log,buf,"Energy of the matrix is %g nm\n",mat_energy(rms));
  if (bUseRmsdCut && (rmsdcut < rms->minrms || rmsdcut > rms->maxrms) )
    fprintf(stderr,"WARNING: rmsd cutoff %g is outside range of rmsd values "
            "%g to %g\n",rmsdcut,rms->minrms,rms->maxrms);
  if (bAnalyze && (rmsmin < rms->minrms) )
    fprintf(stderr,"WARNING: rmsd minimum %g is below lowest rmsd value %g\n",
            rmsmin,rms->minrms);
  if (bAnalyze && (rmsmin > rmsdcut) )
    fprintf(stderr,"WARNING: rmsd minimum %g is above rmsd cutoff %g\n",
            rmsmin,rmsdcut);
  
  /* Plot the rmsd distribution */
  rmsd_distribution(opt2fn("-dist",NFILE,fnm),rms,oenv);
  
  if (bBinary) {
    for(i1=0; (i1 < nf); i1++) 
      for(i2=0; (i2 < nf); i2++)
        if (rms->mat[i1][i2] < rmsdcut)
          rms->mat[i1][i2] = 0;
        else
          rms->mat[i1][i2] = 1;
  }

  snew(clust.cl,nf);
  switch (method) {
  case m_linkage: 
    /* Now sort the matrix and write it out again */
    gather(rms,rmsdcut,&clust);
    break;
  case m_diagonalize:
    /* Do a diagonalization */
      snew(eigval,nf);
      snew(tmp,nf*nf);
      memcpy(tmp,rms->mat[0],nf*nf*sizeof(real));
      eigensolver(tmp,nf,0,nf,eigval,rms->mat[0]);
      sfree(tmp);
      
      fp = xvgropen(opt2fn("-ev",NFILE,fnm),"RMSD matrix Eigenvalues",
                    "Eigenvector index","Eigenvalues (nm\\S2\\N)",oenv);
      for(i=0; (i<nf); i++)
          fprintf(fp,"%10d  %10g\n",i,eigval[i]);
          ffclose(fp);
      break;
  case m_monte_carlo:
    mc_optimize(log,rms,niter,&seed,kT);
    swap_mat(rms);
    reset_index(rms);
    break;
  case m_jarvis_patrick:
    jarvis_patrick(rms->nn,rms->mat,M,P,bJP_RMSD ? rmsdcut : -1,&clust);
    break;
  case m_gromos:
    gromos(rms->nn,rms->mat,rmsdcut,&clust);
    break;
  default:
    gmx_fatal(FARGS,"DEATH HORROR unknown method \"%s\"",methodname[0]);
  }
  
  if (method == m_monte_carlo || method == m_diagonalize)
    fprintf(stderr,"Energy of the matrix after clustering is %g nm\n",
            mat_energy(rms));
  
  if (bAnalyze) {
    if (minstruct > 1) {
      ncluster = plot_clusters(nf,rms->mat,&clust,nlevels,minstruct);
    } else {
      mark_clusters(nf,rms->mat,rms->maxrms,&clust);
    }
    init_t_atoms(&useatoms,isize,FALSE);
    snew(usextps, isize);
    useatoms.resinfo = top.atoms.resinfo;
    for(i=0; i<isize; i++) {
      useatoms.atomname[i]=top.atoms.atomname[index[i]];
      useatoms.atom[i].resind = top.atoms.atom[index[i]].resind;
      useatoms.nres = max(useatoms.nres,useatoms.atom[i].resind+1);
      copy_rvec(xtps[index[i]],usextps[i]);
    }
    useatoms.nr=isize;
    analyze_clusters(nf,&clust,rms->mat,isize,&useatoms,usextps,mass,xx,time,
                     ifsize,fitidx,iosize,outidx,
                     bReadTraj?trx_out_fn:NULL,
                     opt2fn_null("-sz",NFILE,fnm),
                     opt2fn_null("-tr",NFILE,fnm),
                     opt2fn_null("-ntr",NFILE,fnm),
                     opt2fn_null("-clid",NFILE,fnm),
                     bAverage, write_ncl, write_nst, rmsmin, bFit, log,
                     rlo_bot,rhi_bot,oenv);
  }
  ffclose(log);
  
  if (bBinary && !bAnalyze)
    /* Make the clustering visible */
    for(i2=0; (i2 < nf); i2++)
       for(i1=i2+1; (i1 < nf); i1++)
         if (rms->mat[i1][i2])
           rms->mat[i1][i2] = rms->maxrms;

  fp = opt2FILE("-o",NFILE,fnm,"w");
  fprintf(stderr,"Writing rms distance/clustering matrix ");
  if (bReadMat) {
    write_xpm(fp,0,readmat[0].title,readmat[0].legend,readmat[0].label_x,
              readmat[0].label_y,nf,nf,readmat[0].axis_x,readmat[0].axis_y,
              rms->mat,0.0,rms->maxrms,rlo_top,rhi_top,&nlevels);
  } 
  else {
    sprintf(buf,"Time (%s)",output_env_get_time_unit(oenv));
    sprintf(title,"RMS%sDeviation / Cluster Index",
            bRMSdist ? " Distance " : " ");
    if (minstruct > 1) {
      write_xpm_split(fp,0,title,"RMSD (nm)",buf,buf,
                      nf,nf,time,time,rms->mat,0.0,rms->maxrms,&nlevels,
                      rlo_top,rhi_top,0.0,(real) ncluster,
                      &ncluster,TRUE,rlo_bot,rhi_bot);
    } else {
      write_xpm(fp,0,title,"RMSD (nm)",buf,buf,
                nf,nf,time,time,rms->mat,0.0,rms->maxrms,
                rlo_top,rhi_top,&nlevels);
    }
  }
  fprintf(stderr,"\n");
  ffclose(fp);
  
  /* now show what we've done */
  do_view(oenv,opt2fn("-o",NFILE,fnm),"-nxy");
  do_view(oenv,opt2fn_null("-sz",NFILE,fnm),"-nxy");
  if (method == m_diagonalize)
    do_view(oenv,opt2fn_null("-ev",NFILE,fnm),"-nxy");
  do_view(oenv,opt2fn("-dist",NFILE,fnm),"-nxy");
  if (bAnalyze) {
    do_view(oenv,opt2fn_null("-tr",NFILE,fnm),"-nxy");
    do_view(oenv,opt2fn_null("-ntr",NFILE,fnm),"-nxy");
    do_view(oenv,opt2fn_null("-clid",NFILE,fnm),"-nxy");
  }
  
  /* Thank the user for her patience */  
  thanx(stderr);
  
  return 0;
}