g_covar

Main Table of Contents

VERSION 3.1
Thu 28 Feb 2002


Description

g_covar calculates and diagonalizes the (mass-weighted) covariance matrix. All structures are fitted to the structure in the structure file. When this is not a run input file periodicity will not be taken into account. When the fit and analysis groups are identical and the analysis is non mass-weighted, the fit will also be non mass-weighted.

The eigenvectors are written to a trajectory file (-v). When the same atoms are used for the fit and the covariance analysis, the reference structure for the fit is written first with t=-1. The average (or reference when -ref is used) structure is written with t=0, the eigenvectors are written as frames with the eigenvector number as timestamp.

The eigenvectors can be analyzed with g_anaeig.

Option -xpm writes the whole covariance matrix to an xpm file.

Option -xpma writes the atomic covariance matrix to an xpm file, i.e. for each atom pair the sum of the xx, yy and zz covariances is written.

Files

optionfilenametypedescription
-f traj.xtc Input Generic trajectory: xtc trr trj gro g96 pdb
-s topol.tpr Input Structure+mass(db): tpr tpb tpa gro g96 pdb
-n index.ndx Input, Opt. Index file
-o eigenval.xvg Output xvgr/xmgr file
-v eigenvec.trr Output Full precision trajectory: trr trj
-av average.pdb Output Generic structure: gro g96 pdb
-l covar.log Output Log file
-xpm covar.xpm Output, Opt. X PixMap compatible matrix file
-xpma covara.xpm Output, Opt. X PixMap compatible matrix file

Other options

optiontypedefaultdescription
-[no]h bool no Print help info and quit
-[no]X bool no Use dialog box GUI to edit command line options
-nice int 19 Set the nicelevel
-b time -1 First frame (ps) to read from trajectory
-e time -1 Last frame (ps) to read from trajectory
-dt time -1 Only use frame when t MOD dt = first time (ps)
-tu enum ps Time unit: ps, fs, ns, us, ms, s, m or h
-[no]fit bool yes Fit to a reference structure
-[no]ref bool no Use the deviation from the conformation in the structure file instead of from the average
-[no]mwa bool no Mass-weighted covariance analysis
-last int -1 Last eigenvector to write away (-1 is till the last)


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