g_spatial (1) - Linux Man Pages

g_spatial: calculates the spatial distribution function (more control than g_sdf)

NAME

g_spatial - calculates the spatial distribution function (more control than g_sdf)

VERSION 4.0.1

SYNOPSIS

g_spatial -f traj.xtc -s topol.tpr -n index.ndx -dm rmsd.xpm -o rmsd-clust.xpm -g cluster.log -dist rmsd-dist.xvg -ev rmsd-eig.xvg -sz clust-size.xvg -tr clust-trans.xpm -ntr clust-trans.xvg -clid clust-id.xvg -cl clusters.pdb -[no]h -nice int -b time -e time -dt time -tu enum -[no]w -[no]xvgr -[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 -kT real

DESCRIPTION

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 -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.

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 eleminate 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).

FILES

-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 

-dm rmsd.xpm Input, Opt.
 X PixMap compatible matrix file 

-o rmsd-clust.xpm Output
 X PixMap compatible matrix file 

-g cluster.log Output
 Log file 

-dist rmsd-dist.xvg Output, Opt.
 xvgr/xmgr file 

-ev rmsd-eig.xvg Output, Opt.
 xvgr/xmgr file 

-sz clust-size.xvg Output, Opt.
 xvgr/xmgr file 

-tr clust-trans.xpm Output, Opt.
 X PixMap compatible matrix file 

-ntr clust-trans.xvg Output, Opt.
 xvgr/xmgr file 

-clid clust-id.xvg Output, Opt.
 xvgr/xmgr file 

-cl clusters.pdb Output, Opt.
 Trajectory: xtc trr trj gro g96 pdb cpt 

OTHER OPTIONS

-[no]hno
 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

-[no]wno
 View output xvg, xpm, eps and pdb files

-[no]xvgryes
 Add specific codes (legends etc.) in the output xvg files for the xmgrace program

-[no]distano
 Use RMSD of distances instead of RMS deviation

-nlevels int 40
 Discretize RMSD matrix in  levels

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

-[no]fityes
 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]avno
 Write average iso middle structure for each cluster

-wcl int 0
 Write all structures for first  clusters to numbered files

-nst int 1
 Only write all structures if more than  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 or  gromos

-minstruct int 1
 Minimum number of structures in cluster for coloring in the xpm file

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

-M int 10
 Number of nearest neighbors considered for Jarvis-Patrick algorithm, 0 is use cutoff

-P int 3
 Number of identical nearest neighbors required to form a cluster

-seed int 1993
 Random number seed for Monte Carlo clustering algorithm

-niter int 10000
 Number of iterations for MC

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

SEE ALSO

gromacs(7)

More information about GROMACS is available at <http://www.gromacs.org/>.