Man Linux: Main Page and Category List

g_analyze - analyzes data setsVERSION4.0.1

g_analyze-fgraph.xvg-acautocorr.xvg-msdmsd.xvg-cccoscont.xvg-distdistr.xvg-avaverage.xvg-eeerrest.xvg-gfitlog.log-[no]h-niceint-[no]w-[no]xvgr-[no]time-breal-ereal-nint-[no]d-bwreal-errbarenum-[no]integrate-aver_startreal-[no]xydy-[no]regression-[no]luzar-tempreal-fitstartreal-smoothreal-filterreal-[no]power-[no]subav-[no]oneacf-acflenint-[no]normalize-Penum-fitfnenum-ncskipint-beginfitreal-endfitreal

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-avand-powerassume 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-acproduces the autocorrelation function(s). Option-ccplots 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-msdproduces the mean square displacement(s). Option-distproduces distribution plot(s). Option-avproduces 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-eeproduces 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-filterprints 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-gfits the data to the function given with option-fitfn. Option-powerfits 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-luzarperforms a Luzar & Chandler kinetics analysis on output fromg_hbond. The input file can be taken directly fromg_hbond-ac, and then the same result should be produced.

-fgraph.xvgInputxvgr/xmgr file-acautocorr.xvgOutput,Opt.xvgr/xmgr file-msdmsd.xvgOutput,Opt.xvgr/xmgr file-cccoscont.xvgOutput,Opt.xvgr/xmgr file-distdistr.xvgOutput,Opt.xvgr/xmgr file-avaverage.xvgOutput,Opt.xvgr/xmgr file-eeerrest.xvgOutput,Opt.xvgr/xmgr file-gfitlog.logOutput,Opt.Log file

-[no]hnoPrint help info and quit-niceint0Set the nicelevel-[no]wnoView output xvg, xpm, eps and pdb files-[no]xvgryesAdd specific codes (legends etc.) in the output xvg files for the xmgrace program-[no]timeyesExpect a time in the input-breal-1First time to read from set-ereal-1Last time to read from set-nint1Read sets seperated by &-[no]dnoUse the derivative-bwreal0.1Binwidth for the distribution-errbarenumnoneError bars for -av:none,stddev,erroror90-[no]integratenoIntegrate data function(s) numerically using trapezium rule-aver_startreal0Start averaging the integral from here-[no]xydynoInterpret second data set as error in the y values for integrating-[no]regressionnoPerform a linear regression analysis on the data-[no]luzarnoDo 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).-tempreal298.15Temperature for the Luzar hydrogen bonding kinetics analysis-fitstartreal1Time (ps) from which to start fitting the correlation functions in order to obtain the forward and backward rate constants for HB breaking and formation-smoothreal-1If = 0, the tail of the ACF will be smoothed by fitting it to an exponential function: y = A exp(-x/tau)-filterreal0Print the high-frequency fluctuation after filtering with a cosine filter of length-[no]powernoFit data to: b ta-[no]subavyesSubtract the average before autocorrelating-[no]oneacfnoCalculate one ACF over all sets-acflenint-1Length of the ACF, default is half the number of frames-[no]normalizeyesNormalize ACF-Penum0Order of Legendre polynomial for ACF (0 indicates none):0,1,2or3-fitfnenumnoneFit function:none,exp,aexp,exp_exp,vac,exp5,exp7orexp9-ncskipint0Skip N points in the output file of correlation functions-beginfitreal0Time where to begin the exponential fit of the correlation function-endfitreal-1Time where to end the exponential fit of the correlation function, -1 is till the end

gromacs(7)More information aboutGROMACSis available at <http://www.gromacs.org/>. Thu 16 Oct 2008 g_analyze(1)