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# flake8: noqa
import numpy as np
from ase import Atoms
from ase.calculators.gulp import GULP, Conditions
cluster = Atoms(
symbols='O4SiOSiO2SiO2SiO2SiOSiO2SiO3SiO3H8',
pbc=np.array([False, False, False], dtype=bool),
cell=np.array([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]),
positions=np.array(
[
[-1.444348, -0.43209, -2.054785],
[-0.236947, 2.98731, 1.200025],
[3.060238, -1.05911, 0.579909],
[2.958277, -3.289076, 2.027579],
[-0.522747, 0.847624, -2.47521],
[-2.830486, -2.7236, -2.020633],
[-0.764328, -1.251141, 1.402431],
[3.334801, 0.041643, -4.168601],
[-1.35204, -2.009562, 0.075892],
[-1.454655, -1.985635, -1.554533],
[0.85504, 0.298129, -3.159972],
[1.75833, 1.256026, 0.690171],
[2.376446, -0.239522, -2.881245],
[1.806515, -4.484208, -2.686456],
[-0.144193, -2.74503, -2.177778],
[0.167583, 1.582976, 0.47998],
[-1.30716, 1.796853, -3.542121],
[1.441364, -3.072993, -1.958788],
[-1.694171, -1.558913, 2.704219],
[4.417516, 1.263796, 0.563573],
[3.066366, 0.49743, 0.071898],
[-0.704497, 0.351869, 1.102318],
[2.958884, 0.51505, -1.556651],
[1.73983, -3.161794, -0.356577],
[2.131519, -2.336982, 0.996026],
[0.752313, -1.788039, 1.687183],
[-0.142347, 1.685301, -1.12086],
[2.32407, -1.845905, -2.588202],
[-2.571557, -1.937877, 2.604727],
[2.556369, -4.551103, -3.2836],
[3.032586, 0.591698, -4.896276],
[-1.67818, 2.640745, -3.27092],
[5.145483, 0.775188, 0.95687],
[-2.81059, -3.4492, -2.650319],
[2.558023, -3.594544, 2.845928],
[0.400993, 3.469148, 1.733289],
]
),
)
c = Conditions(cluster)
c.min_distance_rule(
'O', 'H', ifcloselabel1='O2', ifcloselabel2='H', elselabel1='O1'
)
calc = GULP(keywords='conp', shel=['O1', 'O2'], conditions=c)
# Single point calculation
cluster.calc = calc
print(cluster.get_potential_energy())
# Optimization using the internal optimizer of GULP
calc.set(keywords='conp opti')
opt = calc.get_optimizer(cluster)
opt.run(fmax=0.05)
print(cluster.get_potential_energy())
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