pele.landscape.LocalConnect#
- class pele.landscape.LocalConnect(pot, mindist, tsSearchParams=None, verbosity=1, NEBparams=None, nrefine_max=100, reoptimize_climbing=0, pushoff_params=None, create_neb=<class 'pele.transition_states._nebdriver.NEBDriver'>)[source]#
a class to do a single local connect run, i.e. NEB + transition state search
- Parameters:
- potpotential object
the potential
- mindistcallable
the function which returns the optimized minimum distance between two structures
- tsSearchParams: dict
parameters passed to the transition state search algorithm
- NEBparamsdict
NEB setup parameters. Use NEBquenchParams for parameters related to the optimization of the band.
- nrefine_maxint
the maximum number of NEB transition state candidates to refine
- reoptimize_climbingint
the number of iterations to use for re-optimizing the climbing images after the NEB is done.
- pushoff_paramsint
parameters for detemining how to find the minima on either side of a transition state
- verbosityint
this controls how many status messages are printed. (not really implemented yet)
See also
DoubleEndedConnectthe routine from which local connect is generally called
pele.transition_states.NEBone of the core routines
pele.transition_states.NEBDriverthe wrapper which sets up NEB
pele.transition_states.findTransitionStateone of the core routine
Notes
this class takes two minima as input, does an NEB run to find transition state candidates, then refines those candidates into transition states. Finally, we fall off either side of the transition states to fine the minima on either side.
This is the core routine of DoubleEndedConnect. It is separated out in order to make parallelization easier. This class intentionally has no knowledge of the global landscape (database, graph, etc.).
Methods
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Attributes