version up

* calculate autocorrelation stats_ineff and tau
* uncorr flag
* read timeseries into vector
* uncorrelate data
* README
* Update README.md
* Update README.md

Co-authored-by: Daniel Bauer <bauer@cbs.tu-darmstadt.de>

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+checksum = "e66366e18dc58b46801afbf2ca7661a9f59cc8c5962c29892b6039b4f86fa992"

Cargo.toml

@@ -1,20 +1,23 @@
 [package]
 name = "wham"
-version = "0.9.1"
-authors = ["D. Bauer <bauer@bio.tu-darmstadt.de>"]
+version = "1.0.0"
+authors = ["Daniel Bauer <bauer@cbs.tu-darmstadt.de>"]
 description = "An implementation of the weighted histogram analysis method"
 license = "GPL-3.0"
 repository = "https://github.com/danijoo/WHAM"
+readme = "README.md"
+categories = ["science", "command-line-utilities", "algorithms"]
+keywords = ["math", "statistics", "histogram", "bioinformatics", "molecular-dynamics"]
 
 [dependencies]
 clap = {version="2.32.0", features=['yaml']}
 error-chain = "0.12.0"
-rand = "0.5.5"
-GSL = "1.0.0"
+rand = "0.7.*"
 rayon = "1.0.3"
 
-[profile.release]
-opt-level = 2
+[dev-dependencies]
+assert_approx_eq = "1.1.0"
+
+[profile.release]
+opt-level = 3
 
-[features]
-default = ["GSL/v2"]

README.md

@@ -1,4 +1,4 @@
-[![Build Status](https://travis-ci.com/danijoo/WHAM.svg?branch=master)](https://travis-ci.com/danijoo/WHAM) [![crates.io](https://img.shields.io/badge/crates.io-orange.svg?longCache=true)](https://www.crates.io/crates/wham) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1488598.svg)](https://doi.org/10.5281/zenodo.1488598)
+[![Build Status](https://travis-ci.com/danijoo/WHAM.svg?branch=master)](https://travis-ci.com/danijoo/WHAM) [![crates.io](https://img.shields.io/badge/crates.io-orange.svg?longCache=true)](https://www.crates.io/crates/wham) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1488597.svg)](https://doi.org/10.5281/zenodo.1488597)
 
 
 
@@ -12,9 +12,10 @@ from umbrella sampling simulations. For more details on the method, I suggest *R
 Features
 ---
 - Fast, especially for small systems
-- Multithreaded
-- Multidimensional
-- Error analysis
+- Multithreaded (automatically runs on all available cores) 
+- Multidimensional (any number of collective variables are possible)
+- Autocorrelation to remove correlated samples
+- Error analysis via bootstrapping
 - Unit tested
 
 Installation
@@ -38,7 +39,67 @@ Usage
 wham has a convenient command line interface. You can see all options with
 ```wham -h```:
 
-To run the two dimensional example (simulation of dialanine phi and psi angle):
+```
+wham 1.0.0
+D. Bauer <bauer@bio.tu-darmstadt.de>
+wham is a fast implementation of the weighted histogram analysis method (WHAM) written in Rust. It currently supports
+potential of mean force (PMF) calculations in multiple dimensions at constant temperature.
+
+Metadata file format:
+    /path/to/timeseries_file1  x_1  x_2  x_N  fc_1  fc_2  fc_N
+    /path/to/timeseries_file2  x_1  x_2  x_N  fc_1  fc_2  fc_N
+    /path/to/timeseries_file3  x_1  x_2  x_N  fc_1  fc_2  fc_N
+The first column is a path to a timeseries file _relative_ to the metadata file (see below). This is followed by the
+position of the umbrella potential x in N dimensions and the force constant fc in each dimension. Lines starting with a
+# are treated as comments and will not be parsed.
+
+Timeseries file format:
+    time  x_1  x_2  x_N
+    time  x_1  x_2  x_N
+    time  x_1  x_2  x_N
+The first column will be ignored and is followed by N reaction coordinates x.
+
+Shipped under the GPLv3 license.
+
+USAGE:
+   wham [FLAGS] [OPTIONS] --bins <BINS> --max <HIST_MAX> --file <METADATA> --min <HIST_MIN> --temperature <temperature>
+
+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.
+
+OPTIONS:
+    -b, --bins <BINS>                  Number of histogram bins (comma separated).
+        --bt <bootstrap>               Number of bayesian bootstrapping runs for error analysis by assigning random
+                                       weights (defaults to 0).
+        --seed <bootstrap_seed>        Random seed for bootstrapping runs.
+        --end <end>                    Skip rows in timeseries with an index larger than this value (defaults to 1e+20)
+    -i, --iterations <ITERATIONS>      Stop WHAM after this many iterations without convergence (defaults to 100,000).
+        --max <HIST_MAX>               Histogram maxima (comma separated). Also accepts "pi".
+    -f, --file <METADATA>              Path to the metadata file.
+        --min <HIST_MIN>               Histogram minima (comma separated for multiple dimensions). Also accepts "pi".
+    -o, --output <output>              Free energy output file (defaults to wham.out).
+        --start <start>                Skip rows in timeseries with an index smaller than this value (defaults to 0)
+    -T, --temperature <temperature>    WHAM temperature in Kelvin.
+    -t, --tolerance <TOLERANCE>        Abortion criteria for WHAM calculation. WHAM stops if abs(F_new - F_old) <
+                                       tolerance (defaults to 0.000001).
+```
+
+Examples
+---
+The example folder contains input and output files for two simple test systems:
+
+- 1d_cyclic: Phi torsion angle of dialanine in vaccum
+- 2d_cyclic: Phi and psi torsion angles of the same system
+
+The command below will run the two dimensional example (simulation of dialanine phi and psi angle) and calculate the free energy based on the two collective variables
+in the range of -3.14 to 3.14, with 100 bins in each dimension and periodic collective variables:
+ 
 ```bash
 wham --max 3.14,3.14 --min -3.14,-3.14 -T 300 --bins 100,100 --cyclic -f example/2d/metadata.dat       
 > Supplied WHAM options: Metadata=example/2d/metadata.dat, hist_min=[-3.14, -3.14], hist_max=[3.14, 3.14], bins=[100, 100] verbose=false, tolerance=0.000001, iterations=100000, temperature=300, cyclic=true
@@ -55,7 +116,6 @@ wham --max 3.14,3.14 --min -3.14,-3.14 -T 300 --bins 100,100 --cyclic -f example
 ```
 After convergence, final bias offsets (F) and the free energy will be dumped to stdout and the output file is written.
 
-
 The output file contains the free energy and probability for each bin. Probabilities are normalized to sum to P=1.0 and
 the smallest free energy is set to 0 (with other free energies based on that).
 ```
@@ -75,26 +135,29 @@ the smallest free energy is set to 0 (with other free energies based on that).
 Error analysis
 ---
 WHAM can perform error analysis using the bayesian bootstrapping method. Every simulation window is assumed to be an
-individual set of data point. By calculating probabilities N times with randomly assigned weights for each window,
+individual set of data points. By calculating probabilities N times with randomly assigned weights for each window,
 one can estimate the error as standard deviation between the N bootstrapping runs. For more details see
 *Van der Spoel, D. et al. (2010). g_wham—A Free Weighted Histogram Analysis Implementation Including Robust Error and
 Autocorrelation Estimates, JCTC, 6(12), 3713-3720*.
 
 To perform bayesian bootstrapping in WHAM, use the ```-bt <RUNS>``` flag to perform <RUNS> individual bootstrapping
-runs. The error estimates of bin probabilities and free energy will be given as separate column (+/-) in the output file.
-If no error analysis is performed, these columns are set to 0.0.
+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.
 
-Examples
+Autocorrelation analysis
 ---
-The example folder contains input and output files for two simple test systems:
+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.
 
-- 1d: Phi torsion angle of dialanine in vaccum
-- 2d: Phi and psi torsion angles of the same system
+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*
 
 
 TODO
 ---
-- Autocorrelation
 - Replica exchange
 
 License & Citing
@@ -102,7 +165,7 @@ License & Citing
 WHAM is licensed under the GPL-3.0 license. Please read the LICENSE file in this
 repository for more information.
 
-There's no publication for this WHAM implementation. However, there is a citeabe DOI. If you use this software for your work, please consider citing it: *Bauer, D, WHAM - An efficient weighted histogram analysis implementation written in Rust, Zenodo.  https://doi.org/10.5281/zenodo.1488597*
+There's no publication for this WHAM implementation. However, there is a citeabe DOI. If you use this software for your work, please consider citing it: *Bauer, D., WHAM - An efficient weighted histogram analysis implementation written in Rust, Zenodo. https://doi.org/10.5281/zenodo.1488597*
 
 Parts of this work, especially some perfomance optimizations and the I/O format, are inspired by the
 implementation of A. Grossfield (*Grossfield, A, WHAM: the weighted histogram analysis method, http://membrane.urmc.rochester.edu/content/wham*).

example/1d/wham.out

@@ -1,101 +0,0 @@
-#coord1    Free Energy    +/-    Probability    +/-
--3.108600    7.118166    0.000000    0.003561    0.000000
--3.045800    5.331290    0.000000    0.007290    0.000000
--2.983000    3.879241    0.000000    0.013048    0.000000
--2.920200    2.968659    0.000000    0.018796    0.000000
--2.857400    1.942494    0.000000    0.028362    0.000000
--2.794600    1.418408    0.000000    0.034994    0.000000
--2.731800    1.169398    0.000000    0.038668    0.000000
--2.669000    0.843024    0.000000    0.044073    0.000000
--2.606200    0.636021    0.000000    0.047887    0.000000
--2.543400    0.720123    0.000000    0.046299    0.000000
--2.480600    1.066434    0.000000    0.040297    0.000000
--2.417800    1.509855    0.000000    0.033734    0.000000
--2.355000    2.015549    0.000000    0.027544    0.000000
--2.292200    2.226942    0.000000    0.025306    0.000000
--2.229400    2.573176    0.000000    0.022026    0.000000
--2.166600    2.591946    0.000000    0.021861    0.000000
--2.103800    2.476835    0.000000    0.022893    0.000000
--2.041000    2.513953    0.000000    0.022555    0.000000
--1.978200    2.470032    0.000000    0.022956    0.000000
--1.915400    2.227585    0.000000    0.025299    0.000000
--1.852600    2.105310    0.000000    0.026570    0.000000
--1.789800    1.778779    0.000000    0.030286    0.000000
--1.727000    1.447127    0.000000    0.034593    0.000000
--1.664200    0.906384    0.000000    0.042968    0.000000
--1.601400    0.304263    0.000000    0.054699    0.000000
--1.538600    0.247397    0.000000    0.055960    0.000000
--1.475800    0.000000    0.000000    0.061795    0.000000
--1.413000    0.536142    0.000000    0.049843    0.000000
--1.350200    1.428046    0.000000    0.034859    0.000000
--1.287400    2.398149    0.000000    0.023627    0.000000
--1.224600    3.784647    0.000000    0.013552    0.000000
--1.161800    5.696583    0.000000    0.006297    0.000000
--1.099000    7.656158    0.000000    0.002870    0.000000
--1.036200    9.955000    0.000000    0.001142    0.000000
--0.973400    12.357407    0.000000    0.000436    0.000000
--0.910600    14.954254    0.000000    0.000154    0.000000
--0.847800    17.745327    0.000000    0.000050    0.000000
--0.785000    20.559461    0.000000    0.000016    0.000000
--0.722200    22.783560    0.000000    0.000007    0.000000
--0.659400    25.175865    0.000000    0.000003    0.000000
--0.596600    26.419980    0.000000    0.000002    0.000000
--0.533800    27.885999    0.000000    0.000001    0.000000
--0.471000    29.029334    0.000000    0.000001    0.000000
--0.408200    30.366556    0.000000    0.000000    0.000000
--0.345400    31.615252    0.000000    0.000000    0.000000
--0.282600    32.781716    0.000000    0.000000    0.000000
--0.219800    33.731378    0.000000    0.000000    0.000000
--0.157000    34.476014    0.000000    0.000000    0.000000
--0.094200    35.387300    0.000000    0.000000    0.000000
--0.031400    35.579756    0.000000    0.000000    0.000000
-0.031400    35.520194    0.000000    0.000000    0.000000
-0.094200    35.344763    0.000000    0.000000    0.000000
-0.157000    34.886460    0.000000    0.000000    0.000000
-0.219800    33.633998    0.000000    0.000000    0.000000
-0.282600    32.686511    0.000000    0.000000    0.000000
-0.345400    31.211777    0.000000    0.000000    0.000000
-0.408200    29.680451    0.000000    0.000000    0.000000
-0.471000    28.032242    0.000000    0.000001    0.000000
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example/1d_cyclic/README.txt

@@ -0,0 +1,9 @@
+Example data: Dialanine torsion angle at 300K
+wham.out was produced with the folling settings:
+
+wham --max pi --min -pi --cyclic\
+    --bins 100 \
+    -T 300 \
+    -f metadata.dat \
+    -o wham.out \
+    --bt 100 --seed 1234

example/1d_cyclic/wham.out

@@ -0,0 +1,101 @@
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example/1d_cyclic/wham_uncorrelated.out

@@ -0,0 +1,101 @@
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