Provided by: gromacs-data_4.6.5-1build1_all bug


       g_anaeig - analyzes the eigenvectors

       VERSION 4.6.5


       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 -[no]version -nice int -b time -e time -dt time  -tu  enum  -[no]w  -xvg
       enum  -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 analysis ( 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  -last.

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

        -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 of 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

        -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

        -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

       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 etc.

       -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

        Print version 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:  fs,  ps,  ns,  us,  ms or  s

        View output  .xvg,  .xpm,  .eps and  .pdb files

       -xvg enum xmgrace
        xvg plot formatting:  xmgrace,  xmgr or  none

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

       -last int -1
        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

       -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 method.

       -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 <>.

                                          Mon 2 Dec 2013                              g_anaeig(1)