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


       g_analyze - analyzes data sets

       VERSION 4.6.5


       g_analyze  -f  graph.xvg -ac autocorr.xvg -msd msd.xvg -cc coscont.xvg -dist distr.xvg -av
       average.xvg -ee errest.xvg -bal ballisitc.xvg -g fitlog.log -[no]h -[no]version -nice  int
       -[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 -smooth real -filter real -[no]power -[no]subav -[no]oneacf -acflen int
       -[no]normalize -P enum -fitfn enum -ncskip int -beginfit real -endfit real


        g_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.

        g_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 y2(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: error2 = 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 f2(t) to error2.  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 ta, 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  g_hbond.  The
       input  file  can  be  taken directly from  g_hbond -ac, and then the same result should be


       -f graph.xvg Input
        xvgr/xmgr file

       -ac autocorr.xvg Output, Opt.
        xvgr/xmgr file

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

       -cc coscont.xvg Output, Opt.
        xvgr/xmgr file

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

       -av average.xvg Output, Opt.
        xvgr/xmgr file

       -ee errest.xvg Output, Opt.
        xvgr/xmgr file

       -bal ballisitc.xvg Output, Opt.
        xvgr/xmgr file

       -g fitlog.log Output, Opt.
        Log file


        Print help info and quit

        Print version info and quit

       -nice int 0
        Set the nicelevel

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

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

        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 &

        Use the derivative

       -bw real 0.1
        Binwidth for the distribution

       -errbar enum none
        Error bars for  -av:  none,  stddev,  error or  90

        Integrate data function(s) numerically using trapezium rule

       -aver_start real 0
        Start averaging the integral from here

        Interpret second data set as error in the y values for integrating

        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 chi2 = (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.

        Do a Luzar and Chandler analysis on a correlation function and  related  as  produced  by
       g_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

       -smooth real -1
        If this value is = 0, the tail  of  the  ACF  will  be  smoothed  by  fitting  it  to  an
       exponential function: y = A exp(-x/tau)

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

        Fit data to: b ta

        Subtract the average before autocorrelating

        Calculate one ACF over all sets

       -acflen int -1
        Length of the ACF, default is half the number of frames

        Normalize ACF

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

       -fitfn enum none
        Fit function:  none,  exp,  aexp,  exp_exp,  vac,  exp5,  exp7,  exp9 or  erffit

       -ncskip int 0
        Skip this many points in the output file of correlation functions

       -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



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                                          Mon 2 Dec 2013                             g_analyze(1)