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gulp_api4ase.py
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"""This module defines an ASE interface to GULP.
Written by:
Andy Cuko <[email protected]>
Antoni Macia <[email protected]>
Modified by:
Shuo Tao <[email protected]>
EXPORT ASE_GULP_COMMAND="/path/to/gulp < PREFIX.gin > PREFIX.got"
Keywords
Options
"""
import os
import re
import numpy as np
from ase.units import eV, Ang
from ase.calculators.calculator import FileIOCalculator, ReadError
class GULPOptimizer:
def __init__(self, atoms, calc):
self.atoms = atoms
self.calc = calc
def todict(self):
return {'type': 'optimization',
'optimizer': 'GULPOptimizer'}
def run(self, fmax=None, steps=None, **gulp_kwargs):
if fmax is not None:
gulp_kwargs['gmax'] = fmax
if steps is not None:
gulp_kwargs['maxcyc'] = steps
self.calc.set(**gulp_kwargs)
self.atoms.calc = self.calc
self.atoms.get_potential_energy()
self.atoms.cell = self.calc.get_atoms().cell
self.atoms.positions[:] = self.calc.get_atoms().positions
class GULP(FileIOCalculator):
implemented_properties = ['energy', 'forces', 'stress']
command = 'gulp < PREFIX.gin > PREFIX.got'
discard_results_on_any_change = True
default_parameters = dict(
keywords='conp gradients',
options=[],
shel=[],
library="library.lib",
conditions=None)
def get_optimizer(self, atoms):
gulp_keywords = self.parameters.keywords.split()
if 'opti' not in gulp_keywords:
raise ValueError('Can only create optimizer from GULP calculator '
'with "opti" keyword. Current keywords: {}'
.format(gulp_keywords))
opt = GULPOptimizer(atoms, self)
return opt
#conditions=[['O', 'default', 'O1'], ['O', 'O2', 'H', '<', '1.6']]
def __init__(self, restart=None,
ignore_bad_restart_file=FileIOCalculator._deprecated,
label='gulp', atoms=None, optimized=None,
Gnorm=1000.0, steps=1000, conditions=None, **kwargs):
"""Construct GULP-calculator object."""
FileIOCalculator.__init__(self, restart, ignore_bad_restart_file,
label, atoms, **kwargs)
self.optimized = optimized
self.core_at = None
self.shel_at = None
self.core_count = None
self.shel_count = None
self.Gnorm = Gnorm
self.steps = steps
self.conditions = conditions
self.library_check()
self.atom_types = []
self.fractional_coordinates = None # GULP prints the fractional coordinates before the Final lattice vectors so they need to be stored and then atoms positions need to be set after we get the Final lattice vectors
def write_input(self, atoms, properties=None, system_changes=None):
FileIOCalculator.write_input(self, atoms, properties, system_changes)
p = self.parameters
# Build string to hold .gin input file:
s = p.keywords
s += '\ntitle\nASE calculation\nend\n\n'
if all(self.atoms.pbc):
cell_params = self.atoms.cell.cellpar()
# Formating is necessary since Gulp max-line-length restriction
s += 'cell\n{0:9.6f} {1:9.6f} {2:9.6f} ' \
'{3:8.5f} {4:8.5f} {5:8.5f}\n'.format(*cell_params)
s += 'frac\n'
coords = self.atoms.get_scaled_positions()
else:
s += 'cart\n'
coords = self.atoms.get_positions()
if self.conditions is not None:
c = self.conditions
labels = c.get_atoms_labels()
self.atom_types = c.get_atom_types()
else:
labels = self.atoms.get_chemical_symbols()
for xyz, symbol in zip(coords, labels):
s += ' {0:2} core' \
' {1:10.7f} {2:10.7f} {3:10.7f}\n' .format(symbol, *xyz)
if symbol in p.shel:
s += ' {0:2} shel' \
' {1:10.7f} {2:10.7f} {3:10.7f}\n' .format(symbol, *xyz)
s += '\nlibrary {0}\n'.format(p.library)
if p.options:
for t in p.options:
s += '%s\n' % t
with open(self.prefix + '.gin', 'w') as fd:
fd.write(s)
def read_results(self):
FileIOCalculator.read(self, self.label)
if not os.path.isfile(self.label + '.got'):
raise ReadError
with open(self.label + '.got') as fd:
lines = fd.readlines()
cycles = -1
self.optimized = None
for i, line in enumerate(lines):
if line.find('Final internal derivatives') != -1:
s = i + 5
core_at = []
shel_at = []
while(True):
s = s + 1
if lines[s].find("------------") != -1:
break
if lines[s].split()[2] == "c":
core_at.append(lines[s].split()[1])
elif lines[s].split()[2] == "s":
shel_at.append(lines[s].split()[1])
# if lines[s].find(" s ") != -1:
# continue
# if lines[s].split()[0]
self.core_at = core_at.copy()
self.shel_at = shel_at.copy()
core_count = {i:core_at.count(i) for i in core_at}
shel_count = {j:shel_at.count(j) for j in shel_at}
self.core_count = core_count.copy()
self.shel_count = shel_count.copy()
# print("core_count", self.core_count)
# print("shel_count", self.shel_count)
# print("core type", list(self.core_count.keys()))
# print("shell type", list(self.shel_count.keys()))
for i, line in enumerate(lines):
m = re.match(r'\s*Total lattice energy\s*=\s*(\S+)\s*eV', line)
if m:
energy = float(m.group(1))
self.results['energy'] = energy
self.results['free_energy'] = energy
elif line.find('Optimisation achieved') != -1:
self.optimized = True
elif line.find('Final Gnorm') != -1:
self.Gnorm = float(line.split()[-1])
elif line.find('Cycle:') != -1:
cycles += 1
elif line.find('Final Cartesian derivatives') != -1:
s = i + 5
forces = []
while(True):
s = s + 1
if lines[s].find("------------") != -1:
break
if lines[s].find(" s ") != -1:
continue
# print(s, lines[s].split()[1] in list(self.shel_count.keys()) )
if lines[s].split()[2] != "s":
if ( lines[s].split()[1] in list(self.core_count.keys()) ) and \
( lines[s].split()[1] not in list(self.shel_count.keys()) ):
g = lines[s].split()[3:6]
G = [-float(x) * eV / Ang for x in g]
forces.append(G)
elif ( lines[s].split()[1] in list(self.core_count.keys()) ) and \
( lines[s].split()[1] in list(self.shel_count.keys()) ):
g_1 = lines[s].split()[3:6]
g_2 = lines[s+self.shel_count[lines[s].split()[1]]].split()[3:6]
G_1 = [-float(x) * eV / Ang for x in g_1]
G_2 = [-float(x) * eV / Ang for x in g_2]
G_tot = np.array(G_1) + np.array(G_2)
forces.append(G_tot.tolist())
# G = [-float(x) * eV / Ang for x in g]
# forces.append(G)
forces = np.array(forces)
self.results['forces'] = forces
# print("shape of forces", self.forces.shape)
# print("forces=\n", self.forces)
elif line.find('Final internal derivatives') != -1:
s = i + 5
forces = []
while(True):
s = s + 1
if lines[s].find("------------") != -1:
break
# if lines[s].find(" s ") != -1:
# continue
# print(s, lines[s].split()[1] in list(self.shel_count.keys()) )
if lines[s].split()[2] != "s":
if ( lines[s].split()[1] in list(self.core_count.keys()) ) and \
( lines[s].split()[1] not in list(self.shel_count.keys()) ):
g = lines[s].split()[3:6]
G = [-float(x) * eV / Ang for x in g]
forces.append(G)
elif ( lines[s].split()[1] in list(self.core_count.keys()) ) and \
( lines[s].split()[1] in list(self.shel_count.keys()) ):
g_1 = lines[s].split()[3:6]
g_2 = lines[s+self.shel_count[lines[s].split()[1]]].split()[3:6]
G_1 = [-float(x) * eV / Ang for x in g_1]
G_2 = [-float(x) * eV / Ang for x in g_2]
G_tot = np.array(G_1) + np.array(G_2)
forces.append(G_tot.tolist())
# G = [-float(x) * eV / Ang for x in g]
# forces.append(G)
forces = np.array(forces)
self.results['forces'] = forces
# print("shape of forces", self.forces.shape)
# print("forces=\n", self.forces)
elif line.find('Final cartesian coordinates of atoms') != -1:
s = i + 5
positions = []
while True:
s = s + 1
if lines[s].find("------------") != -1:
break
if lines[s].find(" s ") != -1:
continue
xyz = lines[s].split()[3:6]
XYZ = [float(x) * Ang for x in xyz]
positions.append(XYZ)
positions = np.array(positions)
self.atoms.set_positions(positions)
elif line.find('Final stress tensor components') != -1:
res = [0., 0., 0., 0., 0., 0.]
for j in range(3):
var = lines[i+j+3].split()[1]
res[j] = float(var)
var = lines[i+j+3].split()[3]
res[j+3] = float(var)
stress = np.array(res)
self.results['stress'] = stress
elif line.find('Final Cartesian lattice vectors') != -1:
lattice_vectors = np.zeros((3, 3))
s = i + 2
for j in range(s, s+3):
temp = lines[j].split()
for k in range(3):
lattice_vectors[j-s][k] = float(temp[k])
self.atoms.set_cell(lattice_vectors)
if self.fractional_coordinates is not None:
self.fractional_coordinates = np.array(self.fractional_coordinates)
self.atoms.set_scaled_positions(self.fractional_coordinates)
elif line.find('Final fractional coordinates of atoms') != -1:
s = i + 5
scaled_positions = []
while True:
s = s + 1
if lines[s].find("------------") != -1:
break
if lines[s].find(" s ") != -1:
continue
xyz = lines[s].split()[3:6]
XYZ = [float(x) for x in xyz]
scaled_positions.append(XYZ)
self.fractional_coordinates = scaled_positions
self.steps = cycles
def get_opt_state(self):
return self.optimized
def get_opt_steps(self):
return self.steps
def get_Gnorm(self):
return self.Gnorm
def library_check(self):
if self.parameters['library'] is not None:
if 'GULP_LIB' not in os.environ:
raise RuntimeError("Be sure to have set correctly $GULP_LIB "
"or to have the force field library.")
class Conditions:
"""Atomic labels for the GULP calculator.
This class manages an array similar to
atoms.get_chemical_symbols() via get_atoms_labels() method, but
with atomic labels in stead of atomic symbols. This is useful
when you need to use calculators like GULP or lammps that use
force fields. Some force fields can have different atom type for
the same element. In this class you can create a set_rule()
function that assigns labels according to structural criteria."""
def __init__(self, atoms):
self.atoms = atoms
self.atoms_symbols = atoms.get_chemical_symbols()
self.atoms_labels = atoms.get_chemical_symbols()
self.atom_types = []
def min_distance_rule(self, sym1, sym2,
ifcloselabel1=None, ifcloselabel2=None,
elselabel1=None, max_distance=3.0):
"""Find pairs of atoms to label based on proximity.
This is for, e.g., the ffsioh or catlow force field, where we
would like to identify those O atoms that are close to H
atoms. For each H atoms, we must specially label one O atom.
This function is a rule that allows to define atom labels (like O1,
O2, O_H etc..) starting from element symbols of an Atoms
object that a force field can use and according to distance
parameters.
Example:
atoms = read('some_xyz_format.xyz')
a = Conditions(atoms)
a.set_min_distance_rule('O', 'H', ifcloselabel1='O2',
ifcloselabel2='H', elselabel1='O1')
new_atoms_labels = a.get_atom_labels()
In the example oxygens O are going to be labeled as O2 if they
are close to a hydrogen atom othewise are labeled O1.
"""
if ifcloselabel1 is None:
ifcloselabel1 = sym1
if ifcloselabel2 is None:
ifcloselabel2 = sym2
if elselabel1 is None:
elselabel1 = sym1
#self.atom_types is a list of element types used instead of element
#symbols in orger to track the changes made. Take care of this because
# is very important.. gulp_read function that parse the output
# has to know which atom_type it has to associate with which
# atom_symbol
#
# Example: [['O','O1','O2'],['H', 'H_C', 'H_O']]
# this because Atoms oject accept only atoms symbols
self.atom_types.append([sym1, ifcloselabel1, elselabel1])
self.atom_types.append([sym2, ifcloselabel2])
dist_mat = self.atoms.get_all_distances()
index_assigned_sym1 = []
index_assigned_sym2 = []
for i in range(len(self.atoms_symbols)):
if self.atoms_symbols[i] == sym2:
dist_12 = 1000
index_assigned_sym2.append(i)
for t in range(len(self.atoms_symbols)):
if (self.atoms_symbols[t] == sym1
and dist_mat[i, t] < dist_12
and t not in index_assigned_sym1):
dist_12 = dist_mat[i, t]
closest_sym1_index = t
index_assigned_sym1.append(closest_sym1_index)
for i1, i2 in zip(index_assigned_sym1, index_assigned_sym2):
if dist_mat[i1, i2] > max_distance:
raise ValueError('Cannot unambiguously apply minimum-distance '
'rule because pairings are not obvious. '
'If you wish to ignore this, then increase '
'max_distance.')
for s in range(len(self.atoms_symbols)):
if s in index_assigned_sym1:
self.atoms_labels[s] = ifcloselabel1
elif s not in index_assigned_sym1 and self.atoms_symbols[s] == sym1:
self.atoms_labels[s] = elselabel1
elif s in index_assigned_sym2:
self.atoms_labels[s] = ifcloselabel2
def get_atom_types(self):
return self.atom_types
def get_atoms_labels(self):
labels = np.array(self.atoms_labels)
return labels