xenial (1) gmx-analyze.1.gz

Provided by: gromacs-data_5.1.2-1ubuntu1_all bug

NAME

       gmx-analyze - Analyze data sets

SYNOPSIS

          gmx analyze [-f [<.xvg>]] [-ac [<.xvg>]] [-msd [<.xvg>]] [-cc [<.xvg>]]
                      [-dist [<.xvg>]] [-av [<.xvg>]] [-ee [<.xvg>]]
                      [-bal [<.xvg>]] [-fitted [<.xvg>]] [-g [<.log>]] [-[no]w]
                      [-xvg <enum>] [-[no]time] [-b <real>] [-e <real>]
                      [-n <int>] [-[no]d] [-bw <real>] [-errbar <enum>]
                      [-[no]integrate] [-aver_start <real>] [-[no]xydy]
                      [-[no]regression] [-[no]luzar] [-temp <real>]
                      [-fitstart <real>] [-fitend <real>] [-filter <real>]
                      [-[no]power] [-[no]subav] [-[no]oneacf] [-acflen <int>]
                      [-[no]normalize] [-P <enum>] [-fitfn <enum>]
                      [-beginfit <real>] [-endfit <real>]

DESCRIPTION

       gmx  analyze  reads an ASCII file and analyzes data sets.  A line in the input file may start with a time
       (see option -time) and any number of y-values may follow.  Multiple sets can also be read when  they  are
       separated  by  &  (option  -n); in this case only one y-value is read from each line.  All lines starting
       with # and @ are skipped.  All analyses can also be done for the derivative of a set (option -d).

       All options, except for -av and -power, assume that the points are equidistant in time.

       gmx analyze always shows the average and standard  deviation  of  each  set,  as  well  as  the  relative
       deviation  of  the third and fourth cumulant from those of a Gaussian distribution with the same standard
       deviation.

       Option -ac produces the autocorrelation function(s).  Be sure that the time interval between data  points
       is much shorter than the time scale of the autocorrelation.

       Option -cc plots the resemblance of set i with a cosine of i/2 periods. The formula is:

          2 (integral from 0 to T of y(t) cos(i pi t) dt)^2 / integral from 0 to T of y^2(t) dt

       This is useful for principal components obtained from covariance analysis, since the principal components
       of random diffusion are pure cosines.

       Option -msd produces the mean square displacement(s).

       Option -dist produces distribution plot(s).

       Option -av produces the average over the sets.  Error bars can be added with  the  option  -errbar.   The
       errorbars  can  represent  the standard deviation, the error (assuming the points are independent) or the
       interval containing 90% of the points, by discarding 5% of the points at the top and the bottom.

       Option -ee produces error estimates using block averaging.  A set is divided in a number  of  blocks  and
       averages  are  calculated for each block. The error for the total average is calculated from the variance
       between averages of the m blocks B_i as follows: error^2 = sum (B_i - <B>)^2 / (m*(m-1)).   These  errors
       are plotted as a function of the block size.  Also an analytical block average curve is plotted, assuming
       that the autocorrelation is a sum of two exponentials.  The analytical curve for the block average is:

          f(t) = sigma``*``sqrt(2/T (  alpha   (tau_1 ((exp(-t/tau_1) - 1) tau_1/t + 1)) +
                                 (1-alpha) (tau_2 ((exp(-t/tau_2) - 1) tau_2/t + 1)))),

       where T is the total time.  alpha, tau_1 and tau_2 are obtained by fitting f^2(t) to error^2.   When  the
       actual  block  average  is very close to the analytical curve, the error is sigma``*``sqrt(2/T (a tau_1 +
       (1-a) tau_2)).  The complete derivation is given in B. Hess, J. Chem. Phys. 116:209-217, 2002.

       Option -bal finds and subtracts the ultrafast "ballistic" component from a hydrogen bond  autocorrelation
       function  by  the  fitting  of a sum of exponentials, as described in e.g.  O. Markovitch, J. Chem. Phys.
       129:084505, 2008. The fastest term is the one with the most negative coefficient in the  exponential,  or
       with  -d, the one with most negative time derivative at time 0.  -nbalexp sets the number of exponentials
       to fit.

       Option -gem fits bimolecular rate  constants  ka  and  kb  (and  optionally  kD)  to  the  hydrogen  bond
       autocorrelation  function  according  to  the  reversible  geminate  recombination  model. Removal of the
       ballistic component first is strongly advised. The model is presented in O. Markovitch,  J.  Chem.  Phys.
       129:084505, 2008.

       Option  -filter prints the RMS high-frequency fluctuation of each set and over all sets with respect to a
       filtered average.  The filter is proportional to cos(pi t/len) where t goes from -len/2 to len/2. len  is
       supplied with the option -filter.  This filter reduces oscillations with period len/2 and len by a factor
       of 0.79 and 0.33 respectively.

       Option -g fits the data to the function given with option -fitfn.

       Option -power fits the data to b t^a, which is accomplished by fitting to a t + b on log-log  scale.  All
       points after the first zero or with a negative value are ignored.

       Option  -luzar performs a Luzar & Chandler kinetics analysis on output from gmx hbond. The input file can
       be taken directly from gmx hbond -ac, and then the same result should be produced.

       Option -fitfn performs curve fitting to a number of different curves that make sense in  the  context  of
       molecular  dynamics, mainly exponential curves. More information is in the manual. To check the output of
       the fitting procedure the option -fitted will print both the original data and the fitted function  to  a
       new data file. The fitting parameters are stored as comment in the output file.

OPTIONS

       Options to specify input files:

       -f [<.xvg>] (graph.xvg)
              xvgr/xmgr file

       Options to specify output files:

       -ac [<.xvg>] (autocorr.xvg) (Optional)
              xvgr/xmgr file

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

       -cc [<.xvg>] (coscont.xvg) (Optional)
              xvgr/xmgr file

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

       -av [<.xvg>] (average.xvg) (Optional)
              xvgr/xmgr file

       -ee [<.xvg>] (errest.xvg) (Optional)
              xvgr/xmgr file

       -bal [<.xvg>] (ballisitc.xvg) (Optional)
              xvgr/xmgr file

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

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

       Other options:

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

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

       -[no]time (yes)
              Expect a time in the input

       -b <real> (-1)
              First time to read from set

       -e <real> (-1)
              Last time to read from set

       -n <int> (1)
              Read this number of sets separated by &

       -[no]d (no)
              Use the derivative

       -bw <real> (0.1)
              Binwidth for the distribution

       -errbar <enum> (none)
              Error bars for -av: none, stddev, error, 90

       -[no]integrate (no)
              Integrate data function(s) numerically using trapezium rule

       -aver_start <real> (0)
              Start averaging the integral from here

       -[no]xydy (no)
              Interpret second data set as error in the y values for integrating

       -[no]regression (no)
              Perform a linear regression analysis on the data. If -xydy is set a second set will be interpreted
              as the error bar in the Y value. Otherwise, if  multiple  data  sets  are  present  a  multilinear
              regression  will be performed yielding the constant A that minimize chi^2 = (y - A_0 x_0 - A_1 x_1
              - ... - A_N x_N)^2 where now Y is the first data set in the input file and x_i the others. Do read
              the information at the option -time.

       -[no]luzar (no)
              Do  a  Luzar and Chandler analysis on a correlation function and related as produced by gmx hbond.
              When in addition the -xydy flag is given the second and  fourth  column  will  be  interpreted  as
              errors in c(t) and n(t).

       -temp <real> (298.15)
              Temperature for the Luzar hydrogen bonding kinetics analysis (K)

       -fitstart <real> (1)
              Time (ps) from which to start fitting the correlation functions in order to obtain the forward and
              backward rate constants for HB breaking and formation

       -fitend <real> (60)
              Time (ps) where to stop fitting the correlation functions in  order  to  obtain  the  forward  and
              backward rate constants for HB breaking and formation. Only with -gem

       -filter <real> (0)
              Print the high-frequency fluctuation after filtering with a cosine filter of this length

       -[no]power (no)
              Fit data to: b t^a

       -[no]subav (yes)
              Subtract the average before autocorrelating

       -[no]oneacf (no)
              Calculate one ACF over all sets

       -acflen <int> (-1)
              Length of the ACF, default is half the number of frames

       -[no]normalize (yes)
              Normalize ACF

       -P <enum> (0)
              Order of Legendre polynomial for ACF (0 indicates none): 0, 1, 2, 3

       -fitfn <enum> (none)
              Fit function: none, exp, aexp, exp_exp, exp5, exp7, exp9

       -beginfit <real> (0)
              Time where to begin the exponential fit of the correlation function

       -endfit <real> (-1)
              Time where to end the exponential fit of the correlation function, -1 is until the end

SEE ALSO

       gmx(1)

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

       2015, GROMACS development team