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README.md
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README.md
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[](https://travis-ci.com/danijoo/WHAM) [](https://www.crates.io/crates/wham)
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[](https://travis-ci.com/danijoo/WHAM) [](https://www.crates.io/crates/wham) [](https://doi.org/10.5281/zenodo.1488598)
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Weighted Histogram Analysis Method (WHAM)
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===
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This is an fast implementation of the weighted histogram analysis method
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written in Rust. It allows the calculation of multidimensional free energy profiles
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from umbrella sampling simulations. For more details on the method, I suggest Roux, B.
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(1995). The calculation of the potential of mena force using computer simulations, CPC, 91(1), 275-282.
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from umbrella sampling simulations. For more details on the method, I suggest *Roux, B.
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(1995). The calculation of the potential of mean force using computer simulations, CPC, 91(1), 275-282.*
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Features
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---
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WHAM can perform error analysis using the bayesian bootstrapping method. Every simulation window is assumed to be an
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individual set of data point. By calculating probabilities N times with randomly assigned weights for each window,
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one can estimate the error as standard deviation between the N bootstrapping runs. For more details see
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van der Spoel, D. et al. (2010). g_wham—A Free Weighted Histogram Analysis Implementation Including Robust Error and
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Autocorrelation Estimates, JCTC, 6(12), 3713-3720.
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*Van der Spoel, D. et al. (2010). g_wham—A Free Weighted Histogram Analysis Implementation Including Robust Error and
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Autocorrelation Estimates, JCTC, 6(12), 3713-3720*.
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To perform bayesian bootstrapping in WHAM, use the ```-bt <RUNS>``` flag to perform <RUNS> individual bootstrapping
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runs. The error estimates of bin probabilities and free energy will be given as separate column (+/-) in the output file.
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- Autocorrelation
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- Replica exchange
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License
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License & Citing
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---
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WHAM is licensed under the GPL-3.0 license. Please read the LICENSE file in this
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repository for more information.
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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*
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Parts of this work, especially some perfomance optimizations and the I/O format, are inspired by the
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implementation of A. Grossfield (*A. Grossfield, "WHAM: the weighted histogram analysis method", http://membrane.urmc.rochester.edu/content/wham*).
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implementation of A. Grossfield (*Grossfield, A, WHAM: the weighted histogram analysis method, http://membrane.urmc.rochester.edu/content/wham*).
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