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Systematic force field optimization.
License: Other
This project forked from leeping/forcebalance
Systematic force field optimization.
License: Other
#==================# #| ForceBalance |# #==================# If you're reading this, you are probably looking for help. :D The ForceBalance project website is located at https://simtk.org/home/forcebalance There is documentation available online in html at: http://leeping.github.io/forcebalance/doc/html/index.html You can also download the documentation in pdf format here: http://leeping.github.io/forcebalance/doc/ForceBalance-Manual.pdf #================================# #| Conda / pip installation |# #================================# As of version 1.7.4, ForceBalance is available as a package on the conda-forge channel. To install the package, make sure you are using an Anaconda/Miniconda Python distribution for Python versions 2.7, 3.5, 3.6, or 3.7, then run: `conda install --strict-channel-priority -c conda-forge forcebalance` This will install ForceBalance and all of the required dependencies. It will not install optional dependencies such as OpenMM, Gromacs, AMBER, Tinker, CCTools/Work Queue, or the Open Force Field toolkit. (Note: If you were installing ForceBalance from the omnia repository previously, you may need to clear your index cache using `conda clean -i`.) Similarly, to install from PyPI (Python Package Index), run the command: `pip install forcebalance` #=========================================# #| Building / installing from source |# #=========================================# To build the package: python setup.py build To install the package: python setup.py install To install the package locally (i.e. if you don't have root permissions), try the following: python setup.py install --user python setup.py install --prefix=$HOME/.local python setup.py install --prefix=/your/favorite/directory export PYTHONPATH=/your/favorite/directory Additionally, the Anaconda/Miniconda distributions are very helpful for setting up a local Python environment. To turn the package into a distributable .tar.bz2 file: python setup.py sdist #========================# #| Published Parameters |# #========================# If you are here to obtain data for a published force field (e.g. AMBER-FB15), you can find it in the Products folder. Please email me at leeping (at) ucdavis (dot) edu if you notice anything that should be added. #=======================# #| Citing ForceBalance |# #=======================# Published work that utilizes ForceBalance should include the following references: Wang L-P, Chen J and Van Voorhis T. "Systematic Parametrization of Polarizable Force Fields from Quantum Chemistry Data." J. Chem. Theory Comput. 2013, 9, 452-460. DOI: 10.1021/ct300826t Wang L-P, Martinez TJ and Pande VS. "Building Force Fields: An Automatic, Systematic, and Reproducible Approach." J. Phys. Chem. Lett. 2014, 5, 1885-1891. DOI: 10.1021/jz500737m Qiu Y, Nerenberg PS, Head-Gordon T and Wang L-P. "Systematic Optimization of Water Models Using Liquid/Vapor Surface Tension Data." J. Phys. Chem. B 2019, 123, 7061-7073. DOI: 10.1021/acs.jpcb.9b05455 #===========================# #| Funding Acknowledgement |# #===========================# The development of this code has been supported in part by the following grants and awards: NIH Grant R01 AI130684-02 ACS-PRF 58158-DNI6 NIH Grant U54 GM072970 Open Force Field Consortium
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