Provided by: gromacs-data_2018.1-1_all bug


       gmx-cluster - Cluster structures


          gmx cluster [-f [<.xtc/.trr/...>]] [-s [<.tpr/.gro/...>]] [-n [<.ndx>]]
                      [-dm [<.xpm>]] [-om [<.xpm>]] [-o [<.xpm>]] [-g [<.log>]]
                      [-dist [<.xvg>]] [-ev [<.xvg>]] [-conv [<.xvg>]]
                      [-sz [<.xvg>]] [-tr [<.xpm>]] [-ntr [<.xvg>]]
                      [-clid [<.xvg>]] [-cl [<.xtc/.trr/...>]] [-b <time>]
                      [-e <time>] [-dt <time>] [-tu <enum>] [-[no]w]
                      [-xvg <enum>] [-[no]dista] [-nlevels <int>]
                      [-cutoff <real>] [-[no]fit] [-max <real>] [-skip <int>]
                      [-[no]av] [-wcl <int>] [-nst <int>] [-rmsmin <real>]
                      [-method <enum>] [-minstruct <int>] [-[no]binary]
                      [-M <int>] [-P <int>] [-seed <int>] [-niter <int>]
                      [-nrandom <int>] [-kT <real>] [-[no]pbc]


       gmx  cluster  can  cluster  structures using several different methods.  Distances between
       structures can be determined from a trajectory or read from an .xpm matrix file  with  the
       -dm  option.   RMS  deviation after fitting or RMS deviation of atom-pair distances can be
       used to define the distance between structures.

       single linkage: add a structure to a cluster when its  distance  to  any  element  of  the
       cluster is less than cutoff.

       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  P  neighbors  in  common.  The
       neighbors of a structure are the M closest structures or all structures within cutoff.

       Monte  Carlo:  reorder the RMSD matrix using Monte Carlo such that the order of the frames
       is using the smallest possible increments.  With this it is  possible  to  make  a  smooth
       animation  going  from  one  structure  to  another  with the largest possible (e.g.) RMSD
       between them, however the intermediate steps should be as small as possible.  Applications
       could  be  to  visualize  a  potential  of mean force ensemble of simulations or a pulling
       simulation.  Obviously  the  user  has  to  prepare  the  trajectory  well  (e.g.  by  not
       superimposing  frames).  The final result can be inspect visually by looking at the matrix
       .xpm file, which should vary smoothly from bottom to top.

       diagonalization: diagonalize the RMSD matrix.

       gromos: use algorithm as described in Daura et al.  (Angew. Chem. Int. Ed.  1999,  38,  pp
       236-240).   Count number of neighbors using cut-off, take structure with largest number of
       neighbors with all its neighbors as cluster and eliminate it from the  pool  of  clusters.
       Repeat for remaining structures in pool.

       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.

       Two output files are always written:

          · -o  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 -minstruct = 1  the  graphical
            depiction  is black when two structures are in the same cluster.  When -minstruct > 1
            different colors will be used for each cluster.

          · -g writes information on the options used and a detailed list  of  all  clusters  and
            their members.

       Additionally, a number of optional output files can be written:

          · -dist writes the RMSD distribution.

          · -ev writes the eigenvectors of the RMSD matrix diagonalization.

          · -sz writes the cluster sizes.

          · -tr writes a matrix of the number transitions between cluster pairs.

          · -ntr writes the total number of transitions to or from each cluster.

          · -clid writes the cluster number as a function of time.

          · -cl  writes  average (with option -av) or central structure of each cluster or writes
            numbered files with cluster members for a selected set of clusters (with option -wcl,
            depends  on  -nst  and  -rmsmin).  The  center of a cluster is the structure with the
            smallest average RMSD from all other structures of the cluster.


       Options to specify input files:

       -f [<.xtc/.trr/…>] (traj.xtc) (Optional)
              Trajectory: xtc trr cpt gro g96 pdb tng

       -s [<.tpr/.gro/…>] (topol.tpr)
              Structure+mass(db): tpr gro g96 pdb brk ent

       -n [<.ndx>] (index.ndx) (Optional)
              Index file

       -dm [<.xpm>] (rmsd.xpm) (Optional)
              X PixMap compatible matrix file

       Options to specify output files:

       -om [<.xpm>] (rmsd-raw.xpm)
              X PixMap compatible matrix file

       -o [<.xpm>] (rmsd-clust.xpm)
              X PixMap compatible matrix file

       -g [<.log>] (cluster.log)
              Log file

       -dist [<.xvg>] (rmsd-dist.xvg) (Optional)
              xvgr/xmgr file

       -ev [<.xvg>] (rmsd-eig.xvg) (Optional)
              xvgr/xmgr file

       -conv [<.xvg>] (mc-conv.xvg) (Optional)
              xvgr/xmgr file

       -sz [<.xvg>] (clust-size.xvg) (Optional)
              xvgr/xmgr file

       -tr [<.xpm>] (clust-trans.xpm) (Optional)
              X PixMap compatible matrix file

       -ntr [<.xvg>] (clust-trans.xvg) (Optional)
              xvgr/xmgr file

       -clid [<.xvg>] (clust-id.xvg) (Optional)
              xvgr/xmgr file

       -cl [<.xtc/.trr/…>] (clusters.pdb) (Optional)
              Trajectory: xtc trr cpt gro g96 pdb tng

       Other options:

       -b <time> (0)
              Time of first frame to read from trajectory (default unit ps)

       -e <time> (0)
              Time of last frame to read from trajectory (default unit ps)

       -dt <time> (0)
              Only use frame when t MOD dt = first time (default unit ps)

       -tu <enum> (ps)
              Unit for time values: fs, ps, ns, us, ms, s

       -[no]w (no)
              View output .xvg, .xpm, .eps and .pdb files

       -xvg <enum> (xmgrace)
              xvg plot formatting: xmgrace, xmgr, none

       -[no]dista (no)
              Use RMSD of distances instead of RMS deviation

       -nlevels <int> (40)
              Discretize RMSD matrix in this number of levels

       -cutoff <real> (0.1)
              RMSD cut-off (nm) for two structures to be neighbor

       -[no]fit (yes)
              Use least squares fitting before RMSD calculation

       -max <real> (-1)
              Maximum level in RMSD matrix

       -skip <int> (1)
              Only analyze every nr-th frame

       -[no]av (no)
              Write average instead of middle structure for each cluster

       -wcl <int> (0)
              Write the structures for this number of clusters to numbered files

       -nst <int> (1)
              Only write all structures if more than this number of structures per cluster

       -rmsmin <real> (0)
              minimum rms difference with rest of cluster for writing structures

       -method <enum> (linkage)
              Method   for   cluster   determination:   linkage,   jarvis-patrick,   monte-carlo,
              diagonalization, gromos

       -minstruct <int> (1)
              Minimum number of structures in cluster for coloring in the .xpm file

       -[no]binary (no)
              Treat  the  RMSD  matrix  as  consisting  of 0 and 1, where the cut-off is given by

       -M <int> (10)
              Number of nearest neighbors considered  for  Jarvis-Patrick  algorithm,  0  is  use

       -P <int> (3)
              Number of identical nearest neighbors required to form a cluster

       -seed <int> (0)
              Random number seed for Monte Carlo clustering algorithm (0 means generate)

       -niter <int> (10000)
              Number of iterations for MC

       -nrandom <int> (0)
              The first iterations for MC may be done complete random, to shuffle the frames

       -kT <real> (0.001)
              Boltzmann  weighting  factor  for  Monte  Carlo optimization (zero turns off uphill

       -[no]pbc (yes)
              PBC check



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