~jmbr/committor

Solver for the committor equation using the finite element method. Uses FEniCS and a potential of mean force obtained by colvars.

3f1cd08 Minor changes to init.py and setup.py.

~jmbr pushed to ~jmbr/committor git

1 year, 1 month ago

0fa1b47 Initial commit

~jmbr pushed to ~jmbr/committor git

1 year, 1 month ago
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Introduction
------------

This is a tool for computing the committor function of a molecular
system. It solves the committor equation using the potential of mean
force as its input. The user can designate arbitrary regions of the
space of collective variables as reactant or product.

This program solves the boundary value problem known as the committor
equation in the biophysics literature using the finite element method
as implemented in the FEniCS library [1]. This tool currently supports
spaces of up to three collective variables and relies on the output
from a simulation using the Adaptive Biasing Force method as obtained
by the colvars program [2].

Installation
------------

First install FEniCS following the instructions in [1], then install
the program by writing:

    python setup.py install

Usage
-----

Invoking the committor command with the --help parameter will show all
the available command-line options.

In order to solve a committor equation, it is necessary to have the
.grad, .pmf, and .est files produced by colvars as well as a
configuration file where the reactant and product subdomains are
defined (currently only spherical domains are supported). An example
of a configuration file can be found in the file
examples/boundaries.cfg.

For example, the command:

  committor --grad-file test/ala3.grad --output committor.pvd \
            --boundaries test/boundaries.cfg --num-cells 128 --verbose

solves a 2D committor equation where the gradient of the potential of
mean force is user-specified (via the files ala3.grad, ala3.grad.pmf,
and ala3.grad.est), the reactant and the product are defined in
boundaries, and the spatial discretization is done using a mesh with
128 cells in each dimension. The resulting files can be visualized and
analyzed in ParaView [3].

References
----------

[1] https://fenicsproject.org/

[2] https://github.com/colvars/colvars

[3] http://www.paraview.org/