def __init__(self,
init_file,
args_str,
param_file,
latency=1.0e-3,
name="",
pars=None,
dopbc=True,
threaded=False):
"""Initialises QUIP.
Args:
pars: Mandatory dictionary, giving the parameters needed by QUIP.
"""
if quippy is None:
info("QUIPPY import failed", verbosity.low)
raise quippy_exc
# a socket to the communication library is created or linked
super(FFQUIP, self).__init__(latency,
name,
pars,
dopbc,
threaded=threaded)
self.init_file = init_file
self.args_str = args_str
self.param_file = param_file
# Initializes an atoms object and the interaction potential
self.atoms = quippy.Atoms(self.init_file)
self.pot = quippy.Potential(self.args_str,
param_filename=self.param_file)
# Initializes the conversion factors from i-pi to QUIP
self.len_conv = unit_to_user("length", "angstrom", 1)
self.energy_conv = unit_to_user("energy", "electronvolt", 1)
self.force_conv = unit_to_user("force", "ev/ang", 1)
import quippy
from ase.io import read, write
import sys
i = sys.argv[1]
calculator = quippy.Potential(
"TB NRL-TB",
param_filename=
"/Users/Cas/.julia/dev/MDLearn/exampleTB_com_surf/quip_params.xml")
at = read(
"/Users/Cas/.julia/dev/MDLearn/exampleTB_com_surf/crash_{}.xyz".format(i))
at.set_calculator(calculator)
at.arrays["force"] = at.get_forces()
at.info["energy"] = at.get_potential_energy()
at.info["config_type"] = "HMD_iter{}".format(i)
write(
"/Users/Cas/.julia/dev/MDLearn/exampleTB_com_surf/crash_conv_{}.xyz".
format(i), at)
i0 = int(i) - 1
al = read(
"/Users/Cas/.julia/dev/MDLearn/exampleTB_com_surf/DB_{}.xyz".format(i0),
":")
al.append(at)
write("/Users/Cas/.julia/dev/MDLearn/exampleTB_com_surf/DB_{}.xyz".format(i),
al)
def center_atoms(atoms, vacuum=None, axis=(0, 1, 2)):
"""
(1) Removes existing vacuum, (2) adds specified vacuum and (3) centers system along specified directions.
Substitute for the screwed up quippy Atoms.center()
"""
if vacuum is not None:
shrink_cell(atoms)
atoms.cell += np.eye(3) * vacuum
axis_mask = [True if ax in axis else False for ax in range(3)]
atoms.positions -= atoms.positions.mean(axis=0) * axis_mask
return
calc = quippy.Potential('IP TS', param_filename="ts_params.xml")
# Load atomic configuration
fld = sys.argv[1].strip()
params.os.chdir(fld)
crack_slab = quippy.Atoms('slab.xyz')
print('Unit slab with %d atoms per unit cell:' % len(crack_slab))
print(crack_slab.cell)
print('')
in_put = raw_input('Perform dry system generation (guess configuration)?')
GUESS_RUN = (in_put in ['y', 'Y', 'yes'])
if GUESS_RUN:
print("Performing dry run...")
else:
def setUp(self):
self.pot = quippy.Potential('IP SW',
param_str="""
<SW_params n_types="2" label="PRB_31_plus_H">
<comment> Stillinger and Weber, Phys. Rev. B 31 p 5262 (1984), extended for other elements </comment>
<per_type_data type="1" atomic_num="1" />
<per_type_data type="2" atomic_num="14" />
<per_pair_data atnum_i="1" atnum_j="1" AA="0.0" BB="0.0"
p="0" q="0" a="1.0" sigma="1.0" eps="0.0" />
<per_pair_data atnum_i="1" atnum_j="14" AA="8.581214" BB="0.0327827"
p="4" q="0" a="1.25" sigma="2.537884" eps="2.1672" />
<per_pair_data atnum_i="14" atnum_j="14" AA="7.049556277" BB="0.6022245584"
p="4" q="0" a="1.80" sigma="2.0951" eps="2.1675" />
<!-- triplet terms: atnum_c is the center atom, neighbours j and k -->
<per_triplet_data atnum_c="1" atnum_j="1" atnum_k="1"
lambda="21.0" gamma="1.20" eps="2.1675" />
<per_triplet_data atnum_c="1" atnum_j="1" atnum_k="14"
lambda="21.0" gamma="1.20" eps="2.1675" />
<per_triplet_data atnum_c="1" atnum_j="14" atnum_k="14"
lambda="21.0" gamma="1.20" eps="2.1675" />
<per_triplet_data atnum_c="14" atnum_j="1" atnum_k="1"
lambda="21.0" gamma="1.20" eps="2.1675" />
<per_triplet_data atnum_c="14" atnum_j="1" atnum_k="14"
lambda="21.0" gamma="1.20" eps="2.1675" />
<per_triplet_data atnum_c="14" atnum_j="14" atnum_k="14"
lambda="21.0" gamma="1.20" eps="2.1675" />
</SW_params>
""")
self.fmax = 1e-4
self.at0 = Diamond('Si', latticeconstant=5.43)
self.at0.set_calculator(self.pot)
# relax initial positions and unit cell
FIRE(StrainFilter(self.at0, mask=[1, 1, 1, 0, 0, 0]),
logfile=None).run(fmax=self.fmax)
self.C_ref = np.array(
[[151.4276439, 76.57244456, 76.57244456, 0., 0., 0.],
[76.57244456, 151.4276439, 76.57244456, 0., 0., 0.],
[76.57244456, 76.57244456, 151.4276439, 0., 0., 0.],
[0., 0., 0., 109.85498798, 0., 0.],
[0., 0., 0., 0., 109.85498798, 0.],
[0., 0., 0., 0., 0., 109.85498798]])
self.C_err_ref = np.array(
[[1.73091718, 1.63682097, 1.63682097, 0., 0., 0.],
[1.63682097, 1.73091718, 1.63682097, 0., 0., 0.],
[1.63682097, 1.63682097, 1.73091718, 0., 0., 0.],
[0., 0., 0., 1.65751232, 0., 0.],
[0., 0., 0., 0., 1.65751232, 0.],
[0., 0., 0., 0., 0., 1.65751232]])
self.C_ref_relaxed = np.array(
[[151.28712587, 76.5394162, 76.5394162, 0., 0., 0.],
[76.5394162, 151.28712587, 76.5394162, 0., 0., 0.],
[76.5394162, 76.5394162, 151.28712587, 0., 0., 0.],
[0., 0., 0., 56.32421772, 0., 0.],
[0., 0., 0., 0., 56.32421772, 0.],
[0., 0., 0., 0., 0., 56.32421772]])
self.C_err_ref_relaxed = np.array(
[[1.17748661, 1.33333615, 1.33333615, 0., 0., 0.],
[1.33333615, 1.17748661, 1.33333615, 0., 0., 0.],
[1.33333615, 1.33333615, 1.17748661, 0., 0., 0.],
[0., 0., 0., 0.18959684, 0., 0.],
[0., 0., 0., 0., 0.18959684, 0.],
[0., 0., 0., 0., 0., 0.18959684]])
#!/usr/local/bin/python
from __future__ import print_function
import numpy as np
import ase
import ase.lattice
from ase.optimize.precon import PreconLBFGS, Exp
# Initialise the atomistic energy model
#
# if your matscipy installation was successful use its fast model, if not, fall back on the slow one
import quippy
calc = quippy.Potential('IP SW', param_filename='ip.parms.SW.xml')
calc.set_calc_args({'local_energy': True})
# Create the structure of the bar. The directions in the function below
# orient the crystal such that the dislocations are easer to see in this
# quasi 2-dimensional geometry. "pbc" refers to "Periodic Boundary Conditions"
# and are set to be active in the Z direction, but not in X and Y
unitcell = ase.lattice.cubic.Diamond(directions=[[1, 1, 1], [1, 1, -2],
[1, -1, 0]],
size=(1, 1, 1),
symbol='Si',
pbc=(1, 1, 1))
# the unit cell is replicated in the X and Y directions, but kept minimal in Z
atoms = unitcell * (10, 30, 1)
# assign the energy model to the atoms object
import quippy
from ase.io import read, write
import sys
i = sys.argv[1]
config_type = sys.argv[2]
calculator = quippy.Potential("TB NRL-TB", param_filename="/Users/Cas/.julia/dev/MDLearn/HMD_surf_vac/quip_params.xml")
at = read("/Users/Cas/.julia/dev/MDLearn/HMD_surf_vac/crash_{}.xyz".format(i))
at.set_calculator(calculator)
at.arrays["force"] = at.get_forces()
at.info["energy"] = at.get_potential_energy()
#at.info["virial"] = -1.0 * at.get_volume() * at.get_stress(voigt=False)
at.info["config_type"] = "HMD_{}".format(config_type)
write("/Users/Cas/.julia/dev/MDLearn/HMD_surf_vac/crash_conv_{}.xyz".format(i), at)
i0 = int(i) - 1
al = read("/Users/Cas/.julia/dev/MDLearn/HMD_surf_vac/DB_{}.xyz".format(i0), ":")
al.append(at)
write("/Users/Cas/.julia/dev/MDLearn/HMD_surf_vac/DB_{}.xyz".format(i), al)
#!/usr/bin/python
# -*- coding: utf-8 -*-
"""Module for comparing enthalpies between different stacking sequences.
"""
#from __future__ import print_function
import quippy
import numpy as np
from numpy import sqrt
from math import tan, pi
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
LJ = quippy.Potential("IP LJ", param_filename="LJ.xml")
# Use sig=1, (atom #14, type 1)
def aparray(sqnc):
"""Returns atom numpy array.
Args:
sqnc (string): polytype stacking sequence to be made into an array
For example, 'abc' or 'abcabcacbacb'.
Returns:
numpy array
"""
z = sqrt(2. / 3)
b = sqrt(3) / 6
c = 1 - b
