From 2876c1dc3a38a3454920601f0d826ef1a8eb7528 Mon Sep 17 00:00:00 2001 From: Daniel Bauer Date: Sun, 25 Oct 2020 20:49:52 +0100 Subject: [PATCH] README --- README.md | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 6553ccd..6b0bc91 100644 --- a/README.md +++ b/README.md @@ -14,6 +14,7 @@ Features - Fast, especially for small systems - Multithreaded - Multidimensional +- Autocorrelation to remove correlated samples - Error analysis - Unit tested @@ -67,6 +68,8 @@ FLAGS: -c, --cyclic For periodic reaction coordinates. If this is set, the first and last coordinate bin in each dimension are treated as neighbors for the bias calculation. -h, --help Prints help information + -g, --uncorr Estimates statistical inefficiency of each timeseries via autocorrelation and removes correlated + samples (default is off). -V, --version Prints version information -v, --verbose Enables verbose output. @@ -85,7 +88,6 @@ OPTIONS: -T, --temperature WHAM temperature in Kelvin. -t, --tolerance Abortion criteria for WHAM calculation. WHAM stops if abs(F_new - F_old) < tolerance (defaults to 0.000001). - ``` To run the two dimensional example (simulation of dialanine phi and psi angle): @@ -134,6 +136,18 @@ To perform bayesian bootstrapping in WHAM, use the ```-bt ``` flag to perf runs. The error estimates of bin probabilities and free energy will be given as standard error (SE) in a separate column (+/-) in the output file. If no error analysis is performed, these columns are set to 0.0. +Autocorrelation analysis +--- +With the ```--uncorr``` flag, WHAM calculates the autocorrelation time ```tau``` for all timeseries and all collective +variables. Timeseries are then filtered based on their highest autocorrelation time to remove correlated samples from +the dataset. This reduces the number of data points but can improve the accuracy of the result. + +For filtering, the statistical inefficiency `g` is calculated: ```g = 1 + 2*tau```, and only every `g`th element of the +timeseries is used for unbiasing. A more detailed description of the method can be found in +*Chodera, J.D. et al. (2007). Use of the weighted histogram analysis method for the analysis of simulated and parallel +tempering simulations, JCTC 3(1):26-41* + + Examples --- The example folder contains input and output files for two simple test systems: