def GULPRelaxation(inputStr):
##for gulp to work. gulp folder must be in the same folder as the script
environ["GULP_LIB"] = "\"" + getcwd() + "/Gulp_40/Libraries/\""
environ["ASE_GULP_COMMAND"] = "\"" + getcwd(
) + "/Gulp_40/Exe/gulp.exe\" < PREFIX.gin > PREFIX.got"
##takes string inputStr and turns it into stepNb, shouldRestartFromScratch listOfAtoms
if len(inputStr) % 4 != 2:
print("Args nb " + str(len(inputStr)))
print(inputStr)
print(
"Not enough args. Args order : stepNb, shouldRestartFromScratch (0 or 1), \n atom list formatted as Name Xpos Ypos Zpos for each atom (example CO2 would be C 0 0 0 O 0 1 1 O 0 1 -1)"
)
return "", False
atomNames = []
atomXYZ = []
stepNb = int(inputStr[0])
shouldRestartFromScratch = int(inputStr[1])
#if restart from scratch, destroy previously known trajectory
if (shouldRestartFromScratch == 1):
my_file = Path('tmp.pckl')
if my_file.is_file():
remove('tmp.pckl')
#create Atoms object to optimize
for i in range(0, math.floor(len(inputStr) / 4)):
atomNames.append(inputStr[4 * i + 2])
atomXYZ.append((float(inputStr[4 * i + 3]), float(inputStr[4 * i + 4]),
float(inputStr[4 * i + 5])))
atoms = Atoms(atomNames, positions=atomXYZ)
c = Conditions(atoms)
#attach calculator
calc = GULP(keywords='conp', library="./Gulp_40/Libraries/reaxff.lib")
atoms.calc = calc
calc.set(keywords='conp opti')
#optimize
opt = calc.get_optimizer(atoms)
opt.run(fmax=0.05)
#io.write('../MoleculeLibrary/tmp.xyz', atoms, format='xyz')
pos = atoms.get_positions()
outStr = ""
for i in range(0, len(atomNames)):
outStr += atomNames[i] + " "
outStr += str(pos[i][0]) + " "
outStr += str(pos[i][1]) + " "
outStr += str(pos[i][2]) + " "
return outStr, True
[ 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())