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       g_anaeig - analyzes the eigenvectors

       VERSION 4.0.1


       g_anaeig  -v eigenvec.trr -v2 eigenvec2.trr -f traj.xtc -s topol.tpr -n
       index.ndx -eig eigenval.xvg -eig2 eigenval2.xvg -comp eigcomp.xvg -rmsf
       eigrmsf.xvg   -proj   proj.xvg  -2d  2dproj.xvg  -3d  3dproj.pdb  -filt
       filtered.xtc  -extr  extreme.pdb  -over  overlap.xvg  -inpr  inprod.xpm
       -[no]h  -nice  int  -b  time -e time -dt time -tu enum -[no]w -[no]xvgr
       -first int -last int  -skip  int  -max  real  -nframes  int  -[no]split
       -[no]entropy -temp real -nevskip int


          g_anaeig  analyzes  eigenvectors.  The  eigenvectors  can  be  of  a
       covariance matrix ( g_covar) or of a Normal Modes anaysis ( g_nmeig).

       When a trajectory is projected  on  eigenvectors,  all  structures  are
       fitted  to the structure in the eigenvector file, if present, otherwise
       to the structure in the structure file.  When  no  run  input  file  is
       supplied, periodicity will not be taken into account. Most analyses are
       performed on eigenvectors  -first to  -last, but when  -first is set to
       -1 you will be prompted for a selection.

         -comp: plot the vector components per atom of eigenvectors  -first to

        -rmsf: plot the RMS fluctuation per atom of eigenvectors    -first  to
       -last (requires  -eig).

         -proj:  calculate projections of a trajectory on eigenvectors  -first
       to  -last.  The projections of a trajectory on the eigenvectors of  its
       covariance  matrix are called principal components (pc’s).  It is often
       useful to check the cosine content the pc’s, since the pc’s  of  random
       diffusion  are  cosines with the number of periods equal to half the pc
       index.  The cosine content of the  pc’s  can  be  calculated  with  the
       program  g_analyze.

        -2d: calculate a 2d projection of a trajectory on eigenvectors  -first
       and  -last.

        -3d: calculate a 3d projection of a  trajectory  on  the  first  three
       selected eigenvectors.

          -filt:   filter  the  trajectory  to  show  only  the  motion  along
       eigenvectors  -first to  -last.

        -extr: calculate the two extreme projections along a trajectory on the
       average structure and interpolate  -nframes frames between them, or set
       your own extremes with  -max. The eigenvector  -first will  be  written
       unless   -first  and  -last have been set explicitly, in which case all
       eigenvectors will be written to separate files. Chain identifiers  will
       be  added  when  writing a  .pdb file with two or three structures (you
       can use  rasmol -nmrpdb to view such a pdb file).

         Overlap calculations between covariance analysis:

         NOTE: the analysis should use the same fitting structure

        -over: calculate the subspace overlap of the eigenvectors in file  -v2
       with eigenvectors  -first to  -last in file  -v.

         -inpr:  calculate  a matrix of inner-products between eigenvectors in
       files  -v and  -v2. All eigenvectors of both files will be used  unless
       -first and  -last have been set explicitly.

       When   -v,   -eig,   -v2  and  -eig2 are given, a single number for the
       overlap between the covariance matrices is generated. The formulas are:

               difference = sqrt(tr((sqrt(M1) - sqrt(M2))2))

       normalized overlap = 1 - difference/sqrt(tr(M1) + tr(M2))

            shape overlap = 1 - sqrt(tr((sqrt(M1/tr(M1)) - sqrt(M2/tr(M2)))2))

       where M1 and M2 are the two covariance matrices and tr is the trace  of
       a  matrix.  The  numbers  are proportional to the overlap of the square
       root of the fluctuations. The normalized overlap  is  the  most  useful
       number, it is 1 for identical matrices and 0 when the sampled subspaces
       are orthogonal.

       When the  -entropy flag is given an entropy estimate will  be  computed
       based on the Quasiharmonic approach and based on Schlitter’s formula.


       -v eigenvec.trr Input
        Full precision trajectory: trr trj cpt

       -v2 eigenvec2.trr Input, Opt.
        Full precision trajectory: trr trj cpt

       -f traj.xtc Input, Opt.
        Trajectory: xtc trr trj gro g96 pdb cpt

       -s topol.tpr Input, Opt.
        Structure+mass(db): tpr tpb tpa gro g96 pdb

       -n index.ndx Input, Opt.
        Index file

       -eig eigenval.xvg Input, Opt.
        xvgr/xmgr file

       -eig2 eigenval2.xvg Input, Opt.
        xvgr/xmgr file

       -comp eigcomp.xvg Output, Opt.
        xvgr/xmgr file

       -rmsf eigrmsf.xvg Output, Opt.
        xvgr/xmgr file

       -proj proj.xvg Output, Opt.
        xvgr/xmgr file

       -2d 2dproj.xvg Output, Opt.
        xvgr/xmgr file

       -3d 3dproj.pdb Output, Opt.
        Structure file: gro g96 pdb

       -filt filtered.xtc Output, Opt.
        Trajectory: xtc trr trj gro g96 pdb cpt

       -extr extreme.pdb Output, Opt.
        Trajectory: xtc trr trj gro g96 pdb cpt

       -over overlap.xvg Output, Opt.
        xvgr/xmgr file

       -inpr inprod.xpm Output, Opt.
        X PixMap compatible matrix file


        Print help info and quit

       -nice int 19
        Set the nicelevel

       -b time 0
        First frame (ps) to read from trajectory

       -e time 0
        Last frame (ps) to read from trajectory

       -dt time 0
        Only use frame when t MOD dt = first time (ps)

       -tu enum ps
        Time unit:  ps,  fs,  ns,  us,  ms or  s

        View output xvg, xpm, eps and pdb files

        Add  specific  codes  (legends  etc.)  in the output xvg files for the
       xmgrace program

       -first int 1
        First eigenvector for analysis (-1 is select)

       -last int 8
        Last eigenvector for analysis (-1 is till the last)

       -skip int 1
        Only analyse every nr-th frame

       -max real 0
        Maximum for projection of the eigenvector on  the  average  structure,
       max=0 gives the extremes

       -nframes int 2
        Number of frames for the extremes output

        Split eigenvector projections where time is zero

        Compute  entropy according to the Quasiharmonic formula or Schlitter’s

       -temp real 298.15
        Temperature for entropy calculations

       -nevskip int 6
        Number of eigenvalues to skip when computing the entropy  due  to  the
       quasi   harmonic   approximation.  When  you  do  a  rotational  and/or
       translational fit prior to the covariance analysis,  you  get  3  or  6
       eigenvalues  that are very close to zero, and which should not be taken
       into account when computing the entropy.



       More     information     about     GROMACS     is     available      at

                                Thu 16 Oct 2008                    g_anaeig(1)