def __init__(self, atoms, restart=None, logfile='-' , trajectory=None, soften = 0, factsoft = 0.7,
outer_optimizer=BFGS, finish_optimizer = GxOptimizer, opt_args=None, relax_max=2, liuconstr = None,
switchfinish = True, treat1 = True, treat2 = True, additionalcoords = [1, 2] ):
"""Structure optimizer object.
source of the code is the following paper:
H.-F. Wang and Z.-P. Liu: Comprehensive Mechanism and Structure-Sensitivity of Ethanol
Oxidation on Platinum: New Transition-State Searching Method for Resolving the Complex
Reaction Network, JACS 130 (2008), 10996
atoms: Atoms object
The Atoms object to relax.
restart: str
Filename for restart file. Default value is *None*.
logfile: file object or str
If *logfile* is a string, a file with that name will be opened.
Use '-' for stdout.
trajectory: Trajectory object or str
Attach trajectory object. If *trajectory* is a string a
PickleTrajectory will be constructed. Use *None* for no
trajectory.
outer_optimizer: optimizer for the "Broyden steps"
opt_args: **opt_args will be given to the outer optimizer, so if
some addiditional arguments are wanted
relax_max: after this amount of steps (integer) an update step
is performed
liuconstr: constraint object
treat1: if true calculate with treatment 1
treat2: if true calculate with treatment 2
soften: there are different implementations of treatment 2, soften
chooses which one to take
factsoft: treatment 2 wants a value, saying how much of change considerd
will be used for adjusting the neighboring atoms, different meaning
for the different soften values
switchfinish: for the finishing of the calculation (if already near TS) there
may be the wanting for another (faster) transition state searcher
finish_optimizer: optimizer which finishes after switchforfinish, will be used after
three update and four additional relaxation steps without any
visible change to the coordinates
"""
Dynamics.__init__(self, atoms, logfile, trajectory)
# set optimizer
if opt_args == None:
self.dyn = outer_optimizer( atoms )
else:
# set optimizer with user given variables
self.dyn = outer_optimizer( atoms, **opt_args)
self.restart = restart
self.relax_max = relax_max
self.stepsmax = None
self.dyn.initialize()
self.liuconstr = liuconstr
self.treat1 = treat1
self.treat2 = treat2
self.soften = soften
self.factsoft = factsoft
self.switchfinish = switchfinish
self.finish_optimizer = finish_optimizer
self.logout = open('liu.output','w')
self.adcoord = additionalcoords
def __init__(self, atoms, timestep, trajectory):
Dynamics.__init__(self, atoms, logfile=None, trajectory=trajectory)
self.dt = timestep
self.masses = self.atoms.get_masses()
self.masses.shape = (-1, 1)
