OPS-based module: Shooting range shooter¶
This module implements the “shooting from the top” algorithm as detailed in the paper “Transition path sampling of rare events by shooting from the top”.
Purpose of Module¶
The purpose of this algorithm is to increase the number of generated transitions in a transition path sampling simulation by exclusively shooting from the transition state ensemble (TSE)/the top of the barrier (hence the name). Naturally this only works if the approximate location of the TSE is already known and can be given as a function of the atomic coordinates. In this module any openpathsampling.Volume object can be used by the user to define the shooting range volume. This enables the user to define the shooting range for example as a function of one or more collective variables. See also the Transition State Ensemble in OpenPathSampling for finding the TSE.
The implementation in this module includes:
- A
ShootingRangeSelector
subclass ofopenpathsampling.ShootingPointSelector
to pick shooting points only in the predefined shooting range volume.
Background Information¶
This module builds on OpenPathSampling, a Python package for path sampling simulations. To learn more about OpenPathSampling, you might be interested in reading:
- OPS documentation: http://openpathsampling.org
- OPS source code: http://github.com/openpathsampling/openpathsampling
Testing¶
Tests in OpenPathSampling and sr_shooter use the nose package.
To test this module you need to first install OpenPathSampling, then download the source files for this package (see the Source Code
section below) and install it using
python setup.py install
or pip install -e .
from the root directory of the package.
In the root folder then type nosetests
to test the module using the nose package.
Examples¶
Source Code¶
The source code for this module can be found in https://gitlab.e-cam2020.eu/hejung/sr_shooter.