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## NAME

```       g_analyze - analyzes data sets

VERSION 4.0.1

```

## SYNOPSIS

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

```

## DESCRIPTION

```       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
seperated 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.
For  each  set  it  also  shows the relative deviation of the third and
forth cumulant from those of a  Gaussian  distribution  with  the  same
standard deviation.

Option  -ac produces the autocorrelation function(s).

Option   -cc  plots  the  resemblance  of  set  i  with a cosine of i/2
periods. The formula is: 2 (int0-T y(t) cos(i pi t) dt)2 / int0-T  y(t)
y(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 (  a   (tau1 ((exp(-t/tau1) - 1) tau1/t + 1)) +

(1-a) (tau2 ((exp(-t/tau2) - 1) tau2/t +  1)))),
where  T  is  the total time.  a, tau1 and tau2 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 tau1 + (1-a) tau2)).
The  complete  derivation  is  given  in  B.  Hess,  J.   Chem.   Phys.
116:209-217, 2002.

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
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 produced.

```

## FILES

```       -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

-g fitlog.log Output, Opt.
Log file

```

## OTHEROPTIONS

```       -[no]hno
Print help info and quit

-nice int 0
Set the nicelevel

-[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]timeyes
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

-[no]dno
Use the derivative

-bw real 0.1
Binwidth for the distribution

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

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

-aver_start real 0
Start averaging the integral from here

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

-[no]regressionno
Perform a linear regression analysis on the data

-[no]luzarno
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

-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

-smooth real -1
If  =  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 length

-[no]powerno
Fit data to: b ta

-[no]subavyes
Subtract the average before autocorrelating

-[no]oneacfno
Calculate one ACF over all sets

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

-[no]normalizeyes
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  or
exp9

-ncskip int 0
Skip N 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 till the end

```

```       gromacs(7)