1GMX-ANALYZE(1) GROMACS GMX-ANALYZE(1)
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6 gmx-analyze - Analyze data sets
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9 gmx analyze [-f [<.xvg>]] [-ac [<.xvg>]] [-msd [<.xvg>]] [-cc [<.xvg>]]
10 [-dist [<.xvg>]] [-av [<.xvg>]] [-ee [<.xvg>]]
11 [-fitted [<.xvg>]] [-g [<.log>]] [-[no]w] [-xvg <enum>]
12 [-[no]time] [-b <real>] [-e <real>] [-n <int>] [-[no]d]
13 [-bw <real>] [-errbar <enum>] [-[no]integrate]
14 [-aver_start <real>] [-[no]xydy] [-[no]regression]
15 [-[no]luzar] [-temp <real>] [-fitstart <real>]
16 [-fitend <real>] [-filter <real>] [-[no]power]
17 [-[no]subav] [-[no]oneacf] [-acflen <int>]
18 [-[no]normalize] [-P <enum>] [-fitfn <enum>]
19 [-beginfit <real>] [-endfit <real>]
20
22 gmx analyze reads an ASCII file and analyzes data sets. A line in the
23 input file may start with a time (see option -time) and any number of
24 y-values may follow. Multiple sets can also be read when they are sep‐
25 arated by & (option -n); in this case only one y-value is read from
26 each line. All lines starting with # and @ are skipped. All analyses
27 can also be done for the derivative of a set (option -d).
28 All options, except for -av and -power, assume that the points are
30 equidistant in time.
31 gmx analyze always shows the average and standard deviation of each
33 set, as well as the relative deviation of the third and fourth cumulant
34 from those of a Gaussian distribution with the same standard deviation.
35 Option -ac produces the autocorrelation function(s). Be sure that the
37 time interval between data points is much shorter than the time scale
38 of the autocorrelation.
39 Option -cc plots the resemblance of set i with a cosine of i/2 periods.
41 The formula is:
42 2 (integral from 0 to T of y(t) cos(i pi t) dt)^2
44 / integral from 0 to T of y^2(t) dt
45 This is useful for principal components obtained from covariance analy‐
47 sis, since the principal components of random diffusion are pure
48 cosines.
49 Option -msd produces the mean square displacement(s).
51 Option -dist produces distribution plot(s).
53 Option -av produces the average over the sets. Error bars can be added
55 with the option -errbar. The errorbars can represent the standard de‐
56 viation, the error (assuming the points are independent) or the inter‐
57 val containing 90% of the points, by discarding 5% of the points at the
58 top and the bottom.
59 Option -ee produces error estimates using block averaging. A set is
61 divided in a number of blocks and averages are calculated for each
62 block. The error for the total average is calculated from the variance
63 between averages of the m blocks B_i as follows: error^2 = sum (B_i -
64 <B>)^2 / (m*(m-1)). These errors are plotted as a function of the
65 block size. Also an analytical block average curve is plotted, assum‐
66 ing that the autocorrelation is a sum of two exponentials. The analyt‐
67 ical curve for the block average is:
68 f(t) = sigma``*``sqrt(2/T ( alpha
70 (tau_1 ((exp(-t/tau_1) - 1)
71 tau_1/t + 1)) +
72 (1-alpha) (tau_2
73 ((exp(-t/tau_2) - 1) tau_2/t +
74 1)))),
75 where T is the total time. alpha, tau_1 and tau_2 are obtained by fit‐
77 ting f^2(t) to error^2. When the actual block average is very close to
78 the analytical curve, the error is sigma``*``sqrt(2/T (a tau_1 + (1-a)
79 tau_2)). The complete derivation is given in B. Hess, J. Chem. Phys.
80 116:209-217, 2002.
81 Option -filter prints the RMS high-frequency fluctuation of each set
83 and over all sets with respect to a filtered average. The filter is
84 proportional to cos(pi t/len) where t goes from -len/2 to len/2. len is
85 supplied with the option -filter. This filter reduces oscillations
86 with period len/2 and len by a factor of 0.79 and 0.33 respectively.
87 Option -g fits the data to the function given with option -fitfn.
89 Option -power fits the data to b t^a, which is accomplished by fitting
91 to a t + b on log-log scale. All points after the first zero or with a
92 negative value are ignored.
93 Option -luzar performs a Luzar & Chandler kinetics analysis on output
95 from gmx hbond. The input file can be taken directly from gmx hbond
96 -ac, and then the same result should be produced.
97 Option -fitfn performs curve fitting to a number of different curves
99 that make sense in the context of molecular dynamics, mainly exponen‐
100 tial curves. More information is in the manual. To check the output of
101 the fitting procedure the option -fitted will print both the original
102 data and the fitted function to a new data file. The fitting parameters
103 are stored as comment in the output file.
104
106 Options to specify input files:
107 -f [<.xvg>] (graph.xvg)
109 xvgr/xmgr file
110 Options to specify output files:
112 -ac [<.xvg>] (autocorr.xvg) (Optional)
114 xvgr/xmgr file
115 -msd [<.xvg>] (msd.xvg) (Optional)
117 xvgr/xmgr file
118 -cc [<.xvg>] (coscont.xvg) (Optional)
120 xvgr/xmgr file
121 -dist [<.xvg>] (distr.xvg) (Optional)
123 xvgr/xmgr file
124 -av [<.xvg>] (average.xvg) (Optional)
126 xvgr/xmgr file
127 -ee [<.xvg>] (errest.xvg) (Optional)
129 xvgr/xmgr file
130 -fitted [<.xvg>] (fitted.xvg) (Optional)
132 xvgr/xmgr file
133 -g [<.log>] (fitlog.log) (Optional)
135 Log file
136 Other options:
138 -[no]w (no)
140 View output .xvg, .xpm, .eps and .pdb files
141 -xvg <enum> (xmgrace)
143 xvg plot formatting: xmgrace, xmgr, none
144 -[no]time (yes)
146 Expect a time in the input
147 -b <real> (-1)
149 First time to read from set
150 -e <real> (-1)
152 Last time to read from set
153 -n <int> (1)
155 Read this number of sets separated by &
156 -[no]d (no)
158 Use the derivative
159 -bw <real> (0.1)
161 Binwidth for the distribution
162 -errbar <enum> (none)
164 Error bars for -av: none, stddev, error, 90
165 -[no]integrate (no)
167 Integrate data function(s) numerically using trapezium rule
168 -aver_start <real> (0)
170 Start averaging the integral from here
171 -[no]xydy (no)
173 Interpret second data set as error in the y values for integrat‐
174 ing
175 -[no]regression (no)
177 Perform a linear regression analysis on the data. If -xydy is
178 set a second set will be interpreted as the error bar in the Y
179 value. Otherwise, if multiple data sets are present a multilin‐
180 ear regression will be performed yielding the constant A that
181 minimize chi^2 = (y - A_0 x_0 - A_1 x_1 - ... - A_N x_N)^2 where
182 now Y is the first data set in the input file and x_i the oth‐
183 ers. Do read the information at the option -time.
184 -[no]luzar (no)
186 Do a Luzar and Chandler analysis on a correlation function and
187 related as produced by gmx hbond. When in addition the -xydy
188 flag is given the second and fourth column will be interpreted
189 as errors in c(t) and n(t).
190 -temp <real> (298.15)
192 Temperature for the Luzar hydrogen bonding kinetics analysis (K)
193 -fitstart <real> (1)
195 Time (ps) from which to start fitting the correlation functions
196 in order to obtain the forward and backward rate constants for
197 HB breaking and formation
198 -fitend <real> (60)
200 Time (ps) where to stop fitting the correlation functions in or‐
201 der to obtain the forward and backward rate constants for HB
202 breaking and formation. Only with -gem
203 -filter <real> (0)
205 Print the high-frequency fluctuation after filtering with a co‐
206 sine filter of this length
207 -[no]power (no)
209 Fit data to: b t^a
210 -[no]subav (yes)
212 Subtract the average before autocorrelating
213 -[no]oneacf (no)
215 Calculate one ACF over all sets
216 -acflen <int> (-1)
218 Length of the ACF, default is half the number of frames
219 -[no]normalize (yes)
221 Normalize ACF
222 -P <enum> (0)
224 Order of Legendre polynomial for ACF (0 indicates none): 0, 1,
225 2, 3
226 -fitfn <enum> (none)
228 Fit function: none, exp, aexp, exp_exp, exp5, exp7, exp9
229 -beginfit <real> (0)
231 Time where to begin the exponential fit of the correlation func‐
232 tion
233 -endfit <real> (-1)
235 Time where to end the exponential fit of the correlation func‐
236 tion, -1 is until the end
237
239 gmx(1)
240 More information about GROMACS is available at <‐
242 http://www.gromacs.org/>.
243
245 2022, GROMACS development team
2462022.2 Jun 16, 2022 GMX-ANALYZE(1)