# g_analyze_d (1) - Linux Man Pages

## g_analyze_d: analyzes data sets

## NAME

g_analyze - analyzes data sets## 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**

**-ac*** autocorr.xvg*
**Output, Opt.**

**-msd*** msd.xvg*
**Output, Opt.**

**-cc*** coscont.xvg*
**Output, Opt.**

**-dist*** distr.xvg*
**Output, Opt.**

**-av*** average.xvg*
**Output, Opt.**

**-ee*** errest.xvg*
**Output, Opt.**

**-g*** fitlog.log*
**Output, Opt.**

## OTHER OPTIONS

**-[no]h**

*no*

**-nice*** int*** 0**

**-[no]w***no *

**-[no]xvgr***yes *

**-[no]time***yes *

**-b*** real*** -1 **

**-e*** real*** -1 **

**-n*** int*** 1**

**-[no]d***no *

**-bw*** real*** 0.1 **

**-errbar*** enum*** none**

** none**,

**,**stddev

error

90

**-[no]integrate***no *

**-aver_start*** real*** 0 **

**-[no]xydy***no *

**-[no]regression***no *

**-[no]luzar***no *

**-temp*** real*** 298.15**

**-fitstart*** real*** 1 **

**-smooth*** real*** -1 **

**-filter*** real*** 0 **

**-[no]power***no *

**-[no]subav***yes *

**-[no]oneacf***no *

**-acflen*** int*** -1**

**-[no]normalize***yes *

**-P*** enum*** 0**

** 0**,

**,**1

2

3

**-fitfn*** enum*** none**

** none**,

**,**exp

**,**aexp

**,**exp_exp

**,**vac

**,**exp5

exp7

exp9

**-ncskip*** int*** 0**

**-beginfit*** real*** 0 **

**-endfit*** real*** -1 **